Job Description Job Description Principal Data Scientist - Remote, AI, Machine Learning, Fraud Detection & Risk Modeling Remote position available to candidates residing in Georgia, South Carolina, North Carolina, Florida, or Tennessee. Preference given to candidates located near our Augusta, GA or Charlotte, NC operations. Principal Data Scientist, Artificial Intelligence (AI), Machine Learning, Fraud Detection, Risk Modeling, Generative AI, Large Language Models (LLMs), Predictive Analytics, MLOps, Python, SQL, Snowflake, Databricks. Who we are: At TaxSlayer, we're more than just a tax software development company; we're empowering individuals and small businesses to plan for and file their tax returns online with confidence and ease. As a leading innovator in tax prep software, TaxSlayer, LLC, has been revolutionizing the way people file their taxes since 1965. Our user-friendly platform offers an intuitive interface that guides customers through the tax-filing process step by step, ensuring accuracy and maximum refunds. TaxSlayer is headquartered in Augusta, GA with a satellite office in Charlotte, NC. TaxSlayer proudly employs nearly 200 individuals year-round, plus 300 additional in-season support agents. Our employees are among the brightest, most talented group of innovators who work collaboratively to improve our products and exceed customer expectations season after season. Are you a TaxSlayer? Job Summary The Principal Data Scientist is a senior technical leader who drives advanced machine learning and data science initiatives across the organization. This role combines hands-on technical expertise with strategic influence. The Principal Data Scientist owns end-to-end delivery of complex ML projects, presents recommendations to leadership, leads technical discussions, and serves as the recognized authority on modeling approaches. The role partners cross-functionally with Product, Engineering, Finance, and Marketing to define and solve high-impact business problems, with particular focus on fraud detection, customer intelligence, and risk modeling. Core Responsibilities Own end-to-end delivery of strategic, high-impact data science projects from problem definition through production deployment, monitoring, and optimization. Lead scoping discussions and present project results as subject-matter authority. Develop and deploy advanced machine learning models for fraud detection, risk assessment, anomaly detection, customer segmentation, and churn prediction. Build real-time scoring pipelines, ensure production reliability, and present model design choices as the authority on their technical merits. Lead fraud detection initiatives, designing detection algorithms, collaborating with compliance and investigation teams, and continuously improving model performance as fraud patterns evolve. Evaluate and apply emerging AI and machine learning technologies, including large language models (LLMs), generative AI, and agentic systems, to enhance product capabilities and competitive advantage. Define and document best practices for model development, testing, and deployment, and present them to stakeholders as the authority on the subject. Design and build scalable data pipelines, feature engineering frameworks, and reusable modeling infrastructure that accelerate model development and deployment across the organization. Monitor model performance, data quality, and business outcomes in production. Identify degradation, troubleshoot issues, drive continuous improvements, and present findings while leading discussions on remediation priorities. Partner with Product, Engineering, Finance, and Marketing teams to define analytical requirements, establish success metrics, and deliver recommendations that drive strategic decision-making. Present complex analytical findings and strategic recommendations to executive leadership and business stakeholders with clarity and confidence. Communicate technical concepts to diverse audiences and drive adoption of data-driven strategies. Ensure all models and analytical processes comply with regulatory, privacy, security, and governance requirements. Collaborate with compliance and legal teams as needed. Stay current on emerging data science, ML, and AI trends. Identify, prototype, and recommend innovations that improve customer experience and competitive position. Contribute to documentation, best practices, architectural decisions, and reusable code libraries that strengthen the organization's data science capabilities. Your Impact in This Role Successful deployment and adoption of advanced ML models that generate measurable business impact (fraud reduction, conversion improvement, risk mitigation, operational efficiency), with results presented clearly to leadership. Demonstrated ability to identify and execute high-impact strategic initiatives independently with minimal direction or coaching, and to lead discussions that align stakeholders on priorities. Clear, confident communication and presentation of complex technical concepts to executives and stakeholders; proven ability to lead discussions, serve as the authority in the room, and influence decisions. Improved data science processes, tooling, and infrastructure that reduce time-to-model and accelerate deployment cycles. Required Qualifications Education & Experience: Master's or PhD degree in a quantitative field (Data Science, Computer Science, Statistics, Mathematics, Physics) or equivalent 8+ years of hands-on industry experience as a Data Scientist, Machine Learning Engineer, or similar role, with experience presenting complex work to senior audiences. Demonstrated success leading multiple end-to-end machine learning projects from ideation through production deployment and monitoring, including presenting outcomes and leading project discussions with stakeholders. Proven track record of self-initiated, high-impact projects executed with full ownership and minimal oversight. Skills & Competencies: Very high proficiency in multiple machine learning methods: supervised learning, unsupervised learning, and deep learning. Able to lead method-selection discussions as the subject matter expert. Advanced expertise in SQL and Python; strong software engineering fundamentals including version control, testing, code design, and distributed systems concepts. Strong proficiency in AI technologies, including experience evaluating, fine-tuning, or deploying large language models (LLMs) and generative AI systems in production. Strong experience with modern ML operations (MLOps), model deployment, monitoring, and serving in production environments; hands-on familiarity with cloud platforms (Snowflake, Databricks, AWS, GCP, or Azure). Strong understanding of statistical analysis, experimentation design, A/B testing, hypothesis testing, and causal inference methodologies. Experience building real-time or near-real-time scoring systems and production ML pipelines. Excellent communication skills: ability to explain complex technical concepts clearly to both technical and non-technical audiences. Strong presentation skills and ability to lead discussions without heavy coaching. Strong cross-functional collaboration and stakeholder management skills. Comfortable influencing decisions and driving adoption across Product, Engineering, Finance, and business teams. Preferred Qualifications: Experience in financial services, tax preparation, SaaS, fintech, or e-commerce industries. Hands-on experience building fraud detection, anomaly detection, or risk modeling systems. Physical & Work Environment Requirements This is a fully remote role (US-based only). Occasional travel within US is required for team collaboration, strategy sessions, and business meetings (estimated 4-6 times per year). Work is performed in a standard office environment with remote flexibility. Must be able to work at a computer for extended periods. What we offer: At TaxSlayer we realize the most important aspects in leading our industry are the bright minds behind everything we do. We are proud to offer our employees a highly competitive, comprehensive, and flexible benefits program. We offer flexible remote and/or hybrid work options when possible, depending on the role. Exempt Salaried employees receive a generous PTO bank, in addition to Paid Holidays. Insurance: Medical, Dental, and Vision insurance offerings from Aetna and SunLife. Options for Employee Only, Employee + Spouse/Domestic Partner, Employee + Children, or Family. 401K with 150% match on up to 3% contribution Performance-based bonus and salary review process Other offerings: Wellness Program, Life Insurance for employee, Long-term and Short-term disability, Critical Illness Insurance, Accident Insurance, Education Assistance, company-paid parking, on-site fitness facility, and a company store. Apply today and don't forget to opt in for text updates from our recruiting team! Please note: As a federal contractor, we are responsible to ensure our employees meet any obligations set forth by the U.S. government. We will inform you of any applicable requirements as they arise. Legal Disclaimers TaxSlayer is an equal opportunity employer and complies with all applicable laws regarding discrimination. Employment is based on qualifications, merit, and business need. . click apply for full job details
11/13/2026
Full time
Job Description Job Description Principal Data Scientist - Remote, AI, Machine Learning, Fraud Detection & Risk Modeling Remote position available to candidates residing in Georgia, South Carolina, North Carolina, Florida, or Tennessee. Preference given to candidates located near our Augusta, GA or Charlotte, NC operations. Principal Data Scientist, Artificial Intelligence (AI), Machine Learning, Fraud Detection, Risk Modeling, Generative AI, Large Language Models (LLMs), Predictive Analytics, MLOps, Python, SQL, Snowflake, Databricks. Who we are: At TaxSlayer, we're more than just a tax software development company; we're empowering individuals and small businesses to plan for and file their tax returns online with confidence and ease. As a leading innovator in tax prep software, TaxSlayer, LLC, has been revolutionizing the way people file their taxes since 1965. Our user-friendly platform offers an intuitive interface that guides customers through the tax-filing process step by step, ensuring accuracy and maximum refunds. TaxSlayer is headquartered in Augusta, GA with a satellite office in Charlotte, NC. TaxSlayer proudly employs nearly 200 individuals year-round, plus 300 additional in-season support agents. Our employees are among the brightest, most talented group of innovators who work collaboratively to improve our products and exceed customer expectations season after season. Are you a TaxSlayer? Job Summary The Principal Data Scientist is a senior technical leader who drives advanced machine learning and data science initiatives across the organization. This role combines hands-on technical expertise with strategic influence. The Principal Data Scientist owns end-to-end delivery of complex ML projects, presents recommendations to leadership, leads technical discussions, and serves as the recognized authority on modeling approaches. The role partners cross-functionally with Product, Engineering, Finance, and Marketing to define and solve high-impact business problems, with particular focus on fraud detection, customer intelligence, and risk modeling. Core Responsibilities Own end-to-end delivery of strategic, high-impact data science projects from problem definition through production deployment, monitoring, and optimization. Lead scoping discussions and present project results as subject-matter authority. Develop and deploy advanced machine learning models for fraud detection, risk assessment, anomaly detection, customer segmentation, and churn prediction. Build real-time scoring pipelines, ensure production reliability, and present model design choices as the authority on their technical merits. Lead fraud detection initiatives, designing detection algorithms, collaborating with compliance and investigation teams, and continuously improving model performance as fraud patterns evolve. Evaluate and apply emerging AI and machine learning technologies, including large language models (LLMs), generative AI, and agentic systems, to enhance product capabilities and competitive advantage. Define and document best practices for model development, testing, and deployment, and present them to stakeholders as the authority on the subject. Design and build scalable data pipelines, feature engineering frameworks, and reusable modeling infrastructure that accelerate model development and deployment across the organization. Monitor model performance, data quality, and business outcomes in production. Identify degradation, troubleshoot issues, drive continuous improvements, and present findings while leading discussions on remediation priorities. Partner with Product, Engineering, Finance, and Marketing teams to define analytical requirements, establish success metrics, and deliver recommendations that drive strategic decision-making. Present complex analytical findings and strategic recommendations to executive leadership and business stakeholders with clarity and confidence. Communicate technical concepts to diverse audiences and drive adoption of data-driven strategies. Ensure all models and analytical processes comply with regulatory, privacy, security, and governance requirements. Collaborate with compliance and legal teams as needed. Stay current on emerging data science, ML, and AI trends. Identify, prototype, and recommend innovations that improve customer experience and competitive position. Contribute to documentation, best practices, architectural decisions, and reusable code libraries that strengthen the organization's data science capabilities. Your Impact in This Role Successful deployment and adoption of advanced ML models that generate measurable business impact (fraud reduction, conversion improvement, risk mitigation, operational efficiency), with results presented clearly to leadership. Demonstrated ability to identify and execute high-impact strategic initiatives independently with minimal direction or coaching, and to lead discussions that align stakeholders on priorities. Clear, confident communication and presentation of complex technical concepts to executives and stakeholders; proven ability to lead discussions, serve as the authority in the room, and influence decisions. Improved data science processes, tooling, and infrastructure that reduce time-to-model and accelerate deployment cycles. Required Qualifications Education & Experience: Master's or PhD degree in a quantitative field (Data Science, Computer Science, Statistics, Mathematics, Physics) or equivalent 8+ years of hands-on industry experience as a Data Scientist, Machine Learning Engineer, or similar role, with experience presenting complex work to senior audiences. Demonstrated success leading multiple end-to-end machine learning projects from ideation through production deployment and monitoring, including presenting outcomes and leading project discussions with stakeholders. Proven track record of self-initiated, high-impact projects executed with full ownership and minimal oversight. Skills & Competencies: Very high proficiency in multiple machine learning methods: supervised learning, unsupervised learning, and deep learning. Able to lead method-selection discussions as the subject matter expert. Advanced expertise in SQL and Python; strong software engineering fundamentals including version control, testing, code design, and distributed systems concepts. Strong proficiency in AI technologies, including experience evaluating, fine-tuning, or deploying large language models (LLMs) and generative AI systems in production. Strong experience with modern ML operations (MLOps), model deployment, monitoring, and serving in production environments; hands-on familiarity with cloud platforms (Snowflake, Databricks, AWS, GCP, or Azure). Strong understanding of statistical analysis, experimentation design, A/B testing, hypothesis testing, and causal inference methodologies. Experience building real-time or near-real-time scoring systems and production ML pipelines. Excellent communication skills: ability to explain complex technical concepts clearly to both technical and non-technical audiences. Strong presentation skills and ability to lead discussions without heavy coaching. Strong cross-functional collaboration and stakeholder management skills. Comfortable influencing decisions and driving adoption across Product, Engineering, Finance, and business teams. Preferred Qualifications: Experience in financial services, tax preparation, SaaS, fintech, or e-commerce industries. Hands-on experience building fraud detection, anomaly detection, or risk modeling systems. Physical & Work Environment Requirements This is a fully remote role (US-based only). Occasional travel within US is required for team collaboration, strategy sessions, and business meetings (estimated 4-6 times per year). Work is performed in a standard office environment with remote flexibility. Must be able to work at a computer for extended periods. What we offer: At TaxSlayer we realize the most important aspects in leading our industry are the bright minds behind everything we do. We are proud to offer our employees a highly competitive, comprehensive, and flexible benefits program. We offer flexible remote and/or hybrid work options when possible, depending on the role. Exempt Salaried employees receive a generous PTO bank, in addition to Paid Holidays. Insurance: Medical, Dental, and Vision insurance offerings from Aetna and SunLife. Options for Employee Only, Employee + Spouse/Domestic Partner, Employee + Children, or Family. 401K with 150% match on up to 3% contribution Performance-based bonus and salary review process Other offerings: Wellness Program, Life Insurance for employee, Long-term and Short-term disability, Critical Illness Insurance, Accident Insurance, Education Assistance, company-paid parking, on-site fitness facility, and a company store. Apply today and don't forget to opt in for text updates from our recruiting team! Please note: As a federal contractor, we are responsible to ensure our employees meet any obligations set forth by the U.S. government. We will inform you of any applicable requirements as they arise. Legal Disclaimers TaxSlayer is an equal opportunity employer and complies with all applicable laws regarding discrimination. Employment is based on qualifications, merit, and business need. . click apply for full job details
Job Description Job Description Genesis10 is currently seeking a Senior Network Automation Engineer for a hybrid contract to hire position with a Global Financial Institution located in Jersey City, NJ, Charlotte, NC, or Chandler, AZ. This role is responsible for building and maintaining automation, AI, and machine learning capabilities that enable intelligent network event handling, incident self-healing, predictive insights, and AI-assisted troubleshooting. The position focuses on developing backend services and workflows that analyze network signals, correlate events, and trigger automated diagnostics or remediation actions in partnership with Network Operations, Monitoring, and Data Science teams. Responsibilities: Design and develop network automation services for event correlation, intelligent troubleshooting, and automated remediation Build automation that supports self-healing use cases, such as automated checks, safe remediation actions, and guided recovery steps Develop backend automation services using Python and Django, with supporting data stores (e.g., Redis) Integrate automation services with monitoring, telemetry, and alerting systems Partner with Network Operations teams to identify repeatable operational patterns suitable for automation Ensure automation workflows include guardrails, validation, and rollback logic for safe use in production Design and productionize machine learning solutions for anomaly detection, event correlation, and root-cause analysis Engineer and curate network telemetry datasets for model-ready transformation Develop AI-assisted troubleshooting capabilities using large language models and retrieval-augmented generation Build and maintain MLOps pipelines for experiment tracking, model validation, deployment, and monitoring Implement responsible AI controls covering explainability, privacy, security, and auditability Requirements: Bachelor's or Master's degree in Computer Science, Engineering, or a related field 8-12 years of experience in network engineering, automation, telemetry, data engineering, or applied analytics Demonstrated experience delivering AI/ML-enabled solutions into production Strong software development experience in Python, including REST APIs, message queues, or workflow engines Experience building backend services using Django or similar frameworks Hands-on experience using Redis or equivalent in-memory data stores Solid understanding of enterprise network operations (routing, switching, wireless, SD-WAN) Strong understanding of supervised and unsupervised machine learning, time-series analysis, anomaly detection, and forecasting Hands-on experience with Python data and ML libraries such as pandas, NumPy, scikit-learn, and PyTorch or TensorFlow Experience developing and consuming generative AI solutions, including prompt engineering, embeddings, and vector search Experience with AI/ML development tooling such as Jupyter, MLflow, containers, Kubernetes, and CI/CD pipelines Knowledge of responsible AI, secure AI engineering, data privacy, and model governance Desired skills: Experience with event correlation, rule-based automation, or decision-oriented workflows Familiarity with observability data (metrics, logs, events) as automation inputs Exposure to Infrastructure as Code and CI/CD practices Understanding of IT service management and incident workflows Experience applying AIOps techniques to network assurance or autonomous operations Experience with cloud AI/ML services or GPU-enabled workloads Familiarity with graph analytics or knowledge graphs for root-cause analysis Pay range: $63.68 - $71.68 per hour Only candidates available and ready to work directly as Genesis10 employees will be considered for this position. If you have the described qualifications and are interested in this exciting opportunity, please apply! Ranked a Top Staffing Firm in the U.S. by Staffing Industry Analysts for six consecutive years, Genesis10 puts thousands of consultants and employees to work across the United States every year in contract, contract-for-hire, and permanent placement roles. With more than 300 active clients, Genesis10 provides access to many of the Fortune 100 firms and a variety of mid-market organizations across the full spectrum of industry verticals. For contract roles, Genesis10 offers the benefits listed below. If this is a perm-placement opportunity, our recruiter can talk you through the unique benefits offered for that particular client. Benefits of Working with Genesis10: Access to hundreds of clients, most who have been working with Genesis10 for 5-20+ years. The opportunity to have a career-home in Genesis10; many of our consultants have been working exclusively with Genesis10 for years. Access to an experienced, caring recruiting team (more than 7 years of experience, on average.) Behavioral Health Platform Medical, Dental, Vision Health Savings Account Voluntary Hospital Indemnity (Critical Illness & Accident) Voluntary Term Life Insurance 401K Sick Pay (for applicable states/municipalities) Commuter Benefits (Dallas, NYC, SF, and Illinois) For multiple years running, Genesis10 has been recognized as a Top Staffing Firm in the U.S., as a Best Company for Work-Life Balance, as a Best Company for Career Growth, for Diversity, and for Leadership, amongst others. To learn more and to view all our available career opportunities, please visit us at our website. Genesis10 is an Equal Opportunity Employer. Candidates will receive consideration without regard to their race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or status as a protected veteran.
11/12/2026
Full time
Job Description Job Description Genesis10 is currently seeking a Senior Network Automation Engineer for a hybrid contract to hire position with a Global Financial Institution located in Jersey City, NJ, Charlotte, NC, or Chandler, AZ. This role is responsible for building and maintaining automation, AI, and machine learning capabilities that enable intelligent network event handling, incident self-healing, predictive insights, and AI-assisted troubleshooting. The position focuses on developing backend services and workflows that analyze network signals, correlate events, and trigger automated diagnostics or remediation actions in partnership with Network Operations, Monitoring, and Data Science teams. Responsibilities: Design and develop network automation services for event correlation, intelligent troubleshooting, and automated remediation Build automation that supports self-healing use cases, such as automated checks, safe remediation actions, and guided recovery steps Develop backend automation services using Python and Django, with supporting data stores (e.g., Redis) Integrate automation services with monitoring, telemetry, and alerting systems Partner with Network Operations teams to identify repeatable operational patterns suitable for automation Ensure automation workflows include guardrails, validation, and rollback logic for safe use in production Design and productionize machine learning solutions for anomaly detection, event correlation, and root-cause analysis Engineer and curate network telemetry datasets for model-ready transformation Develop AI-assisted troubleshooting capabilities using large language models and retrieval-augmented generation Build and maintain MLOps pipelines for experiment tracking, model validation, deployment, and monitoring Implement responsible AI controls covering explainability, privacy, security, and auditability Requirements: Bachelor's or Master's degree in Computer Science, Engineering, or a related field 8-12 years of experience in network engineering, automation, telemetry, data engineering, or applied analytics Demonstrated experience delivering AI/ML-enabled solutions into production Strong software development experience in Python, including REST APIs, message queues, or workflow engines Experience building backend services using Django or similar frameworks Hands-on experience using Redis or equivalent in-memory data stores Solid understanding of enterprise network operations (routing, switching, wireless, SD-WAN) Strong understanding of supervised and unsupervised machine learning, time-series analysis, anomaly detection, and forecasting Hands-on experience with Python data and ML libraries such as pandas, NumPy, scikit-learn, and PyTorch or TensorFlow Experience developing and consuming generative AI solutions, including prompt engineering, embeddings, and vector search Experience with AI/ML development tooling such as Jupyter, MLflow, containers, Kubernetes, and CI/CD pipelines Knowledge of responsible AI, secure AI engineering, data privacy, and model governance Desired skills: Experience with event correlation, rule-based automation, or decision-oriented workflows Familiarity with observability data (metrics, logs, events) as automation inputs Exposure to Infrastructure as Code and CI/CD practices Understanding of IT service management and incident workflows Experience applying AIOps techniques to network assurance or autonomous operations Experience with cloud AI/ML services or GPU-enabled workloads Familiarity with graph analytics or knowledge graphs for root-cause analysis Pay range: $63.68 - $71.68 per hour Only candidates available and ready to work directly as Genesis10 employees will be considered for this position. If you have the described qualifications and are interested in this exciting opportunity, please apply! Ranked a Top Staffing Firm in the U.S. by Staffing Industry Analysts for six consecutive years, Genesis10 puts thousands of consultants and employees to work across the United States every year in contract, contract-for-hire, and permanent placement roles. With more than 300 active clients, Genesis10 provides access to many of the Fortune 100 firms and a variety of mid-market organizations across the full spectrum of industry verticals. For contract roles, Genesis10 offers the benefits listed below. If this is a perm-placement opportunity, our recruiter can talk you through the unique benefits offered for that particular client. Benefits of Working with Genesis10: Access to hundreds of clients, most who have been working with Genesis10 for 5-20+ years. The opportunity to have a career-home in Genesis10; many of our consultants have been working exclusively with Genesis10 for years. Access to an experienced, caring recruiting team (more than 7 years of experience, on average.) Behavioral Health Platform Medical, Dental, Vision Health Savings Account Voluntary Hospital Indemnity (Critical Illness & Accident) Voluntary Term Life Insurance 401K Sick Pay (for applicable states/municipalities) Commuter Benefits (Dallas, NYC, SF, and Illinois) For multiple years running, Genesis10 has been recognized as a Top Staffing Firm in the U.S., as a Best Company for Work-Life Balance, as a Best Company for Career Growth, for Diversity, and for Leadership, amongst others. To learn more and to view all our available career opportunities, please visit us at our website. Genesis10 is an Equal Opportunity Employer. Candidates will receive consideration without regard to their race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or status as a protected veteran.
Job Description Job Description Company Description About AbbVie AbbVie's mission is to discover and deliver innovative medicines and solutions that solve serious health issues today and address the medical challenges of tomorrow. We strive to have a remarkable impact on people's lives across several key therapeutic areas including immunology, oncology and neuroscience - and products and services in our Allergan Aesthetics portfolio. For more information about AbbVie, please visit us at . on LinkedIn, Facebook, Instagram, X and YouTube. Job Description The Principal Data Scientist is the senior technical and scientific leader for AbbVie's omnichannel engagement analytics, a data and analytics-driven engagement optimization program spanning channel mix, content, field representative call planning, and orchestration. Operating within the APEX Enterprise Advanced Analytics and Innovation team, this role sets the multi-year science vision for personalized commercial engagement and is accountable for the technical strategy, methodology, and scientific rigor of the AI/ML and statistical solutions that power it. Reporting to the Associate Director, Data Science, the Principal is a thought partner to commercial and analytics leadership: shaping which problems are worth solving, forming and defending a point of view on how AI creates measurable business value, and partnering with product owners to turn that vision into scalable solutions. The role combines deep, hands-on expertise in applied machine learning, generative AI, causal inference, and experimentation with the consultative skill to align a complex stakeholder ecosystem around the right answer. Key Responsibilities Define the Data Science vision: Own the multi-year Data Science vision and technical roadmap for omnichannel engagement analytics, anticipating where both the business and the field of AI are heading. Shape how AI creates business value: identify, size, and prioritize opportunities where AI can drive measurable commercial impact, build the business case, and influence senior leadership decisions on where to invest. Lead hands-on with Gen-AI: Personally use AI-assisted development and agentic tools to prototype, test hypotheses, and demonstrate value quickly; build LLM-backed systems using advanced RAG and context engineering, paired with rigorous scientific evaluation frameworks to scale highly reliable omnichannel recommendations. Lead the design of predictive and causal models: Develop next-best-action, recommendation, and sequential decision models that inform customer engagement and resource allocation using complex, multi-source data. Own measurement science: set the standard for measuring effectiveness, incrementality, and business impact using experimental and quasi-experimental methods, so that AI investments are evaluated rigorously. Partner with product owners to shape problems, not just fulfill requirements: co-define business outcomes, scope, and success metrics, and translate them into scalable technical solutions. Navigate a complex stakeholder ecosystem: build alignment across brand and marketing leaders, field sales and operations, Medical, Legal and Regulatory (MLR), Compliance, BTS, Digital Lab, and external vendors; reframe requests into well-posed problems and resolve competing priorities. Communicate with executive impact: translate complex methods and findings into clear recommendations and compelling narratives for executive and non-technical audiences. Productionize at scale: Partner with BTS, Digital Lab, engineering, and platform teams to deploy, monitor, and manage the lifecycle of AI/ML solutions. Raise the bar for scientific rigor: establish best practices in model development, code quality, reproducibility, peer review, and responsible AI across the data science community. Be a thought leader: stay at the forefront of research and practice in machine learning, generative AI, and causal inference; bring new ideas into the team; provoke rigorous analytical debate; and represent AbbVie's point of view internally and in the broader analytics community. Supervisory / Management Responsibilities This role does not carry formal direct report responsibilities but is expected to act as a technical leader and mentor across the broader data science community, raising the bar on scientific rigor and hands-on AI practice. The Principal Data Scientist may lead technical workstreams with external analytics vendors and partners, including oversight of deliverable quality and methodology validation. Key Competencies Scientific Engineering Depth: Deep expertise in machine learning, causal inference, and generative AI, combined with strong engineering discipline in reproducibility, deployment, and enterprise integration. AI Fluency and Bias to Action: Uses AI hands-on in daily work to prototype, analyze, and build; critically evaluates AI output; and turns ideas into working solutions quickly. Business Judgment and Problem-Framing: Translates ambiguous business challenges into well-scoped problems, connects technical choices to commercial value, and sets long-term technical direction while staying close to delivery. Stakeholder Navigation and Executive Influence: Reads organizational dynamics to build alignment across commercial, regulatory, and technology partners, earning trust as a thought partner to win support from senior leaders. Thought Leadership: Challenges conventional thinking and sparks meaningful analytical debate with peers and executives. Qualifications Education Bachelor's Degree in Statistics, Mathematics, Computer Science, Engineering, or another quantitative discipline required; Master's or PhD in a quantitative field strongly preferred. Required Experience 8+ years of experience in data science, machine learning, or applied science (or 6+ years with a PhD), with a track record of delivering production-quality models that drove measurable business impact. Demonstrated experience setting technical direction for a portfolio of AI/ML solutions and influencing decisions of senior business leaders. Experience building personalization, recommendation, decision-optimization, or marketing-science solutions, in any industry. Deep hands-on expertise in causal inference and experimentation, including A/B testing and quasi-experimental methods, to measure business impact. Demonstrated hands-on experience using generative AI and AI-assisted development tools (e.g., LLM APIs, AI coding assistants, agent frameworks) to prototype and deliver solutions, with concrete examples that can be walked through during the interview process. Expert proficiency in Python and SQL, with experience in deep learning frameworks (e.g., PyTorch, TensorFlow) and distributed data processing. Experience productionizing AI/ML solutions in cloud environments, including deployment, monitoring, and lifecycle management. Track record of leading initiatives across complex, cross-functional stakeholder environments and presenting to executive audiences. Preferred Experience Commercial analytics experience in pharmaceutical, biotech, healthcare, or life sciences, including familiarity with data sources such as IQVIA, Symphony Health, APLD, or similar Rx, claims, and engagement data. Experience in omnichannel analytics, such as journey analysis, touchpoint measurement, closed-loop measurement, or next-best-action for HCP or patient engagement. Experience with advanced ML and optimization methods, including reinforcement learning, multi-armed bandits, transformers, and other approaches for sequential or recommendation use cases. Experience building LLM-based and agentic AI systems, including orchestration frameworks, evaluation, and integration through APIs and pipelines. Experience with cloud ML platforms and MLOps tools such as Azure ML, Databricks, and MLflow. External visibility through conference talks, publications, patents, open-source contributions, or recognized industry thought leadership. Experience working in agile product development environments. Additional Information Applicable only to applicants applying to a position in any location with pay disclosure requirements under state or local law: The compensation range described below is the range of possible base pay compensation that the Company believes in good faith it will pay for this role at the time of this posting based on the job grade for this position. Individual compensation paid within this range will depend on many factors including geographic location, and we may ultimately pay more or less than the posted range. This range may be modified in the future. We offer a comprehensive package of benefits including paid time off (vacation, holidays, sick), medical/dental/vision insurance and 401(k) to eligible employees. This job is eligible to participate in our long-term incentive programs. Note: No amount of pay is considered to be wages or compensation until such amount is earned, vested, and determinable. The amount and availability of any bonus, commission, incentive, benefits, or any other form of compensation and benefits that are allocable to a particular employee remains in the Company's sole and absolute discretion unless and until paid and may be modified at the Company's sole and absolute discretion, consistent with applicable law. AbbVie is an equal opportunity employer and is committed to operating with integrity . click apply for full job details
11/11/2026
Full time
Job Description Job Description Company Description About AbbVie AbbVie's mission is to discover and deliver innovative medicines and solutions that solve serious health issues today and address the medical challenges of tomorrow. We strive to have a remarkable impact on people's lives across several key therapeutic areas including immunology, oncology and neuroscience - and products and services in our Allergan Aesthetics portfolio. For more information about AbbVie, please visit us at . on LinkedIn, Facebook, Instagram, X and YouTube. Job Description The Principal Data Scientist is the senior technical and scientific leader for AbbVie's omnichannel engagement analytics, a data and analytics-driven engagement optimization program spanning channel mix, content, field representative call planning, and orchestration. Operating within the APEX Enterprise Advanced Analytics and Innovation team, this role sets the multi-year science vision for personalized commercial engagement and is accountable for the technical strategy, methodology, and scientific rigor of the AI/ML and statistical solutions that power it. Reporting to the Associate Director, Data Science, the Principal is a thought partner to commercial and analytics leadership: shaping which problems are worth solving, forming and defending a point of view on how AI creates measurable business value, and partnering with product owners to turn that vision into scalable solutions. The role combines deep, hands-on expertise in applied machine learning, generative AI, causal inference, and experimentation with the consultative skill to align a complex stakeholder ecosystem around the right answer. Key Responsibilities Define the Data Science vision: Own the multi-year Data Science vision and technical roadmap for omnichannel engagement analytics, anticipating where both the business and the field of AI are heading. Shape how AI creates business value: identify, size, and prioritize opportunities where AI can drive measurable commercial impact, build the business case, and influence senior leadership decisions on where to invest. Lead hands-on with Gen-AI: Personally use AI-assisted development and agentic tools to prototype, test hypotheses, and demonstrate value quickly; build LLM-backed systems using advanced RAG and context engineering, paired with rigorous scientific evaluation frameworks to scale highly reliable omnichannel recommendations. Lead the design of predictive and causal models: Develop next-best-action, recommendation, and sequential decision models that inform customer engagement and resource allocation using complex, multi-source data. Own measurement science: set the standard for measuring effectiveness, incrementality, and business impact using experimental and quasi-experimental methods, so that AI investments are evaluated rigorously. Partner with product owners to shape problems, not just fulfill requirements: co-define business outcomes, scope, and success metrics, and translate them into scalable technical solutions. Navigate a complex stakeholder ecosystem: build alignment across brand and marketing leaders, field sales and operations, Medical, Legal and Regulatory (MLR), Compliance, BTS, Digital Lab, and external vendors; reframe requests into well-posed problems and resolve competing priorities. Communicate with executive impact: translate complex methods and findings into clear recommendations and compelling narratives for executive and non-technical audiences. Productionize at scale: Partner with BTS, Digital Lab, engineering, and platform teams to deploy, monitor, and manage the lifecycle of AI/ML solutions. Raise the bar for scientific rigor: establish best practices in model development, code quality, reproducibility, peer review, and responsible AI across the data science community. Be a thought leader: stay at the forefront of research and practice in machine learning, generative AI, and causal inference; bring new ideas into the team; provoke rigorous analytical debate; and represent AbbVie's point of view internally and in the broader analytics community. Supervisory / Management Responsibilities This role does not carry formal direct report responsibilities but is expected to act as a technical leader and mentor across the broader data science community, raising the bar on scientific rigor and hands-on AI practice. The Principal Data Scientist may lead technical workstreams with external analytics vendors and partners, including oversight of deliverable quality and methodology validation. Key Competencies Scientific Engineering Depth: Deep expertise in machine learning, causal inference, and generative AI, combined with strong engineering discipline in reproducibility, deployment, and enterprise integration. AI Fluency and Bias to Action: Uses AI hands-on in daily work to prototype, analyze, and build; critically evaluates AI output; and turns ideas into working solutions quickly. Business Judgment and Problem-Framing: Translates ambiguous business challenges into well-scoped problems, connects technical choices to commercial value, and sets long-term technical direction while staying close to delivery. Stakeholder Navigation and Executive Influence: Reads organizational dynamics to build alignment across commercial, regulatory, and technology partners, earning trust as a thought partner to win support from senior leaders. Thought Leadership: Challenges conventional thinking and sparks meaningful analytical debate with peers and executives. Qualifications Education Bachelor's Degree in Statistics, Mathematics, Computer Science, Engineering, or another quantitative discipline required; Master's or PhD in a quantitative field strongly preferred. Required Experience 8+ years of experience in data science, machine learning, or applied science (or 6+ years with a PhD), with a track record of delivering production-quality models that drove measurable business impact. Demonstrated experience setting technical direction for a portfolio of AI/ML solutions and influencing decisions of senior business leaders. Experience building personalization, recommendation, decision-optimization, or marketing-science solutions, in any industry. Deep hands-on expertise in causal inference and experimentation, including A/B testing and quasi-experimental methods, to measure business impact. Demonstrated hands-on experience using generative AI and AI-assisted development tools (e.g., LLM APIs, AI coding assistants, agent frameworks) to prototype and deliver solutions, with concrete examples that can be walked through during the interview process. Expert proficiency in Python and SQL, with experience in deep learning frameworks (e.g., PyTorch, TensorFlow) and distributed data processing. Experience productionizing AI/ML solutions in cloud environments, including deployment, monitoring, and lifecycle management. Track record of leading initiatives across complex, cross-functional stakeholder environments and presenting to executive audiences. Preferred Experience Commercial analytics experience in pharmaceutical, biotech, healthcare, or life sciences, including familiarity with data sources such as IQVIA, Symphony Health, APLD, or similar Rx, claims, and engagement data. Experience in omnichannel analytics, such as journey analysis, touchpoint measurement, closed-loop measurement, or next-best-action for HCP or patient engagement. Experience with advanced ML and optimization methods, including reinforcement learning, multi-armed bandits, transformers, and other approaches for sequential or recommendation use cases. Experience building LLM-based and agentic AI systems, including orchestration frameworks, evaluation, and integration through APIs and pipelines. Experience with cloud ML platforms and MLOps tools such as Azure ML, Databricks, and MLflow. External visibility through conference talks, publications, patents, open-source contributions, or recognized industry thought leadership. Experience working in agile product development environments. Additional Information Applicable only to applicants applying to a position in any location with pay disclosure requirements under state or local law: The compensation range described below is the range of possible base pay compensation that the Company believes in good faith it will pay for this role at the time of this posting based on the job grade for this position. Individual compensation paid within this range will depend on many factors including geographic location, and we may ultimately pay more or less than the posted range. This range may be modified in the future. We offer a comprehensive package of benefits including paid time off (vacation, holidays, sick), medical/dental/vision insurance and 401(k) to eligible employees. This job is eligible to participate in our long-term incentive programs. Note: No amount of pay is considered to be wages or compensation until such amount is earned, vested, and determinable. The amount and availability of any bonus, commission, incentive, benefits, or any other form of compensation and benefits that are allocable to a particular employee remains in the Company's sole and absolute discretion unless and until paid and may be modified at the Company's sole and absolute discretion, consistent with applicable law. AbbVie is an equal opportunity employer and is committed to operating with integrity . click apply for full job details
Job Description Job Description Company Description About AbbVie AbbVie's mission is to discover and deliver innovative medicines and solutions that solve serious health issues today and address the medical challenges of tomorrow. We strive to have a remarkable impact on people's lives across several key therapeutic areas including immunology, oncology and neuroscience - and products and services in our Allergan Aesthetics portfolio. For more information about AbbVie, please visit us at . on LinkedIn, Facebook, Instagram, X and YouTube. Job Description The Principal Data Scientist is the senior technical and scientific leader for AbbVie's omnichannel engagement analytics, a data and analytics-driven engagement optimization program spanning channel mix, content, field representative call planning, and orchestration. Operating within the APEX Enterprise Advanced Analytics and Innovation team, this role sets the multi-year science vision for personalized commercial engagement and is accountable for the technical strategy, methodology, and scientific rigor of the AI/ML and statistical solutions that power it. Reporting to the Associate Director, Data Science, the Principal is a thought partner to commercial and analytics leadership: shaping which problems are worth solving, forming and defending a point of view on how AI creates measurable business value, and partnering with product owners to turn that vision into scalable solutions. The role combines deep, hands-on expertise in applied machine learning, generative AI, causal inference, and experimentation with the consultative skill to align a complex stakeholder ecosystem around the right answer. Key Responsibilities Define the Data Science vision: Own the multi-year Data Science vision and technical roadmap for omnichannel engagement analytics, anticipating where both the business and the field of AI are heading. Shape how AI creates business value: identify, size, and prioritize opportunities where AI can drive measurable commercial impact, build the business case, and influence senior leadership decisions on where to invest. Lead hands-on with Gen-AI: Personally use AI-assisted development and agentic tools to prototype, test hypotheses, and demonstrate value quickly; build LLM-backed systems using advanced RAG and context engineering, paired with rigorous scientific evaluation frameworks to scale highly reliable omnichannel recommendations. Lead the design of predictive and causal models: Develop next-best-action, recommendation, and sequential decision models that inform customer engagement and resource allocation using complex, multi-source data. Own measurement science: set the standard for measuring effectiveness, incrementality, and business impact using experimental and quasi-experimental methods, so that AI investments are evaluated rigorously. Partner with product owners to shape problems, not just fulfill requirements: co-define business outcomes, scope, and success metrics, and translate them into scalable technical solutions. Navigate a complex stakeholder ecosystem: build alignment across brand and marketing leaders, field sales and operations, Medical, Legal and Regulatory (MLR), Compliance, BTS, Digital Lab, and external vendors; reframe requests into well-posed problems and resolve competing priorities. Communicate with executive impact: translate complex methods and findings into clear recommendations and compelling narratives for executive and non-technical audiences. Productionize at scale: Partner with BTS, Digital Lab, engineering, and platform teams to deploy, monitor, and manage the lifecycle of AI/ML solutions. Raise the bar for scientific rigor: establish best practices in model development, code quality, reproducibility, peer review, and responsible AI across the data science community. Be a thought leader: stay at the forefront of research and practice in machine learning, generative AI, and causal inference; bring new ideas into the team; provoke rigorous analytical debate; and represent AbbVie's point of view internally and in the broader analytics community. Supervisory / Management Responsibilities This role does not carry formal direct report responsibilities but is expected to act as a technical leader and mentor across the broader data science community, raising the bar on scientific rigor and hands-on AI practice. The Principal Data Scientist may lead technical workstreams with external analytics vendors and partners, including oversight of deliverable quality and methodology validation. Key Competencies Scientific Engineering Depth: Deep expertise in machine learning, causal inference, and generative AI, combined with strong engineering discipline in reproducibility, deployment, and enterprise integration. AI Fluency and Bias to Action: Uses AI hands-on in daily work to prototype, analyze, and build; critically evaluates AI output; and turns ideas into working solutions quickly. Business Judgment and Problem-Framing: Translates ambiguous business challenges into well-scoped problems, connects technical choices to commercial value, and sets long-term technical direction while staying close to delivery. Stakeholder Navigation and Executive Influence: Reads organizational dynamics to build alignment across commercial, regulatory, and technology partners, earning trust as a thought partner to win support from senior leaders. Thought Leadership: Challenges conventional thinking and sparks meaningful analytical debate with peers and executives. Qualifications Education Bachelor's Degree in Statistics, Mathematics, Computer Science, Engineering, or another quantitative discipline required; Master's or PhD in a quantitative field strongly preferred. Required Experience 8+ years of experience in data science, machine learning, or applied science (or 6+ years with a PhD), with a track record of delivering production-quality models that drove measurable business impact. Demonstrated experience setting technical direction for a portfolio of AI/ML solutions and influencing decisions of senior business leaders. Experience building personalization, recommendation, decision-optimization, or marketing-science solutions, in any industry. Deep hands-on expertise in causal inference and experimentation, including A/B testing and quasi-experimental methods, to measure business impact. Demonstrated hands-on experience using generative AI and AI-assisted development tools (e.g., LLM APIs, AI coding assistants, agent frameworks) to prototype and deliver solutions, with concrete examples that can be walked through during the interview process. Expert proficiency in Python and SQL, with experience in deep learning frameworks (e.g., PyTorch, TensorFlow) and distributed data processing. Experience productionizing AI/ML solutions in cloud environments, including deployment, monitoring, and lifecycle management. Track record of leading initiatives across complex, cross-functional stakeholder environments and presenting to executive audiences. Preferred Experience Commercial analytics experience in pharmaceutical, biotech, healthcare, or life sciences, including familiarity with data sources such as IQVIA, Symphony Health, APLD, or similar Rx, claims, and engagement data. Experience in omnichannel analytics, such as journey analysis, touchpoint measurement, closed-loop measurement, or next-best-action for HCP or patient engagement. Experience with advanced ML and optimization methods, including reinforcement learning, multi-armed bandits, transformers, and other approaches for sequential or recommendation use cases. Experience building LLM-based and agentic AI systems, including orchestration frameworks, evaluation, and integration through APIs and pipelines. Experience with cloud ML platforms and MLOps tools such as Azure ML, Databricks, and MLflow. External visibility through conference talks, publications, patents, open-source contributions, or recognized industry thought leadership. Experience working in agile product development environments. Additional Information Applicable only to applicants applying to a position in any location with pay disclosure requirements under state or local law: The compensation range described below is the range of possible base pay compensation that the Company believes in good faith it will pay for this role at the time of this posting based on the job grade for this position. Individual compensation paid within this range will depend on many factors including geographic location, and we may ultimately pay more or less than the posted range. This range may be modified in the future. We offer a comprehensive package of benefits including paid time off (vacation, holidays, sick), medical/dental/vision insurance and 401(k) to eligible employees. This job is eligible to participate in our long-term incentive programs. Note: No amount of pay is considered to be wages or compensation until such amount is earned, vested, and determinable. The amount and availability of any bonus, commission, incentive, benefits, or any other form of compensation and benefits that are allocable to a particular employee remains in the Company's sole and absolute discretion unless and until paid and may be modified at the Company's sole and absolute discretion, consistent with applicable law. AbbVie is an equal opportunity employer and is committed to operating with integrity . click apply for full job details
11/11/2026
Full time
Job Description Job Description Company Description About AbbVie AbbVie's mission is to discover and deliver innovative medicines and solutions that solve serious health issues today and address the medical challenges of tomorrow. We strive to have a remarkable impact on people's lives across several key therapeutic areas including immunology, oncology and neuroscience - and products and services in our Allergan Aesthetics portfolio. For more information about AbbVie, please visit us at . on LinkedIn, Facebook, Instagram, X and YouTube. Job Description The Principal Data Scientist is the senior technical and scientific leader for AbbVie's omnichannel engagement analytics, a data and analytics-driven engagement optimization program spanning channel mix, content, field representative call planning, and orchestration. Operating within the APEX Enterprise Advanced Analytics and Innovation team, this role sets the multi-year science vision for personalized commercial engagement and is accountable for the technical strategy, methodology, and scientific rigor of the AI/ML and statistical solutions that power it. Reporting to the Associate Director, Data Science, the Principal is a thought partner to commercial and analytics leadership: shaping which problems are worth solving, forming and defending a point of view on how AI creates measurable business value, and partnering with product owners to turn that vision into scalable solutions. The role combines deep, hands-on expertise in applied machine learning, generative AI, causal inference, and experimentation with the consultative skill to align a complex stakeholder ecosystem around the right answer. Key Responsibilities Define the Data Science vision: Own the multi-year Data Science vision and technical roadmap for omnichannel engagement analytics, anticipating where both the business and the field of AI are heading. Shape how AI creates business value: identify, size, and prioritize opportunities where AI can drive measurable commercial impact, build the business case, and influence senior leadership decisions on where to invest. Lead hands-on with Gen-AI: Personally use AI-assisted development and agentic tools to prototype, test hypotheses, and demonstrate value quickly; build LLM-backed systems using advanced RAG and context engineering, paired with rigorous scientific evaluation frameworks to scale highly reliable omnichannel recommendations. Lead the design of predictive and causal models: Develop next-best-action, recommendation, and sequential decision models that inform customer engagement and resource allocation using complex, multi-source data. Own measurement science: set the standard for measuring effectiveness, incrementality, and business impact using experimental and quasi-experimental methods, so that AI investments are evaluated rigorously. Partner with product owners to shape problems, not just fulfill requirements: co-define business outcomes, scope, and success metrics, and translate them into scalable technical solutions. Navigate a complex stakeholder ecosystem: build alignment across brand and marketing leaders, field sales and operations, Medical, Legal and Regulatory (MLR), Compliance, BTS, Digital Lab, and external vendors; reframe requests into well-posed problems and resolve competing priorities. Communicate with executive impact: translate complex methods and findings into clear recommendations and compelling narratives for executive and non-technical audiences. Productionize at scale: Partner with BTS, Digital Lab, engineering, and platform teams to deploy, monitor, and manage the lifecycle of AI/ML solutions. Raise the bar for scientific rigor: establish best practices in model development, code quality, reproducibility, peer review, and responsible AI across the data science community. Be a thought leader: stay at the forefront of research and practice in machine learning, generative AI, and causal inference; bring new ideas into the team; provoke rigorous analytical debate; and represent AbbVie's point of view internally and in the broader analytics community. Supervisory / Management Responsibilities This role does not carry formal direct report responsibilities but is expected to act as a technical leader and mentor across the broader data science community, raising the bar on scientific rigor and hands-on AI practice. The Principal Data Scientist may lead technical workstreams with external analytics vendors and partners, including oversight of deliverable quality and methodology validation. Key Competencies Scientific Engineering Depth: Deep expertise in machine learning, causal inference, and generative AI, combined with strong engineering discipline in reproducibility, deployment, and enterprise integration. AI Fluency and Bias to Action: Uses AI hands-on in daily work to prototype, analyze, and build; critically evaluates AI output; and turns ideas into working solutions quickly. Business Judgment and Problem-Framing: Translates ambiguous business challenges into well-scoped problems, connects technical choices to commercial value, and sets long-term technical direction while staying close to delivery. Stakeholder Navigation and Executive Influence: Reads organizational dynamics to build alignment across commercial, regulatory, and technology partners, earning trust as a thought partner to win support from senior leaders. Thought Leadership: Challenges conventional thinking and sparks meaningful analytical debate with peers and executives. Qualifications Education Bachelor's Degree in Statistics, Mathematics, Computer Science, Engineering, or another quantitative discipline required; Master's or PhD in a quantitative field strongly preferred. Required Experience 8+ years of experience in data science, machine learning, or applied science (or 6+ years with a PhD), with a track record of delivering production-quality models that drove measurable business impact. Demonstrated experience setting technical direction for a portfolio of AI/ML solutions and influencing decisions of senior business leaders. Experience building personalization, recommendation, decision-optimization, or marketing-science solutions, in any industry. Deep hands-on expertise in causal inference and experimentation, including A/B testing and quasi-experimental methods, to measure business impact. Demonstrated hands-on experience using generative AI and AI-assisted development tools (e.g., LLM APIs, AI coding assistants, agent frameworks) to prototype and deliver solutions, with concrete examples that can be walked through during the interview process. Expert proficiency in Python and SQL, with experience in deep learning frameworks (e.g., PyTorch, TensorFlow) and distributed data processing. Experience productionizing AI/ML solutions in cloud environments, including deployment, monitoring, and lifecycle management. Track record of leading initiatives across complex, cross-functional stakeholder environments and presenting to executive audiences. Preferred Experience Commercial analytics experience in pharmaceutical, biotech, healthcare, or life sciences, including familiarity with data sources such as IQVIA, Symphony Health, APLD, or similar Rx, claims, and engagement data. Experience in omnichannel analytics, such as journey analysis, touchpoint measurement, closed-loop measurement, or next-best-action for HCP or patient engagement. Experience with advanced ML and optimization methods, including reinforcement learning, multi-armed bandits, transformers, and other approaches for sequential or recommendation use cases. Experience building LLM-based and agentic AI systems, including orchestration frameworks, evaluation, and integration through APIs and pipelines. Experience with cloud ML platforms and MLOps tools such as Azure ML, Databricks, and MLflow. External visibility through conference talks, publications, patents, open-source contributions, or recognized industry thought leadership. Experience working in agile product development environments. Additional Information Applicable only to applicants applying to a position in any location with pay disclosure requirements under state or local law: The compensation range described below is the range of possible base pay compensation that the Company believes in good faith it will pay for this role at the time of this posting based on the job grade for this position. Individual compensation paid within this range will depend on many factors including geographic location, and we may ultimately pay more or less than the posted range. This range may be modified in the future. We offer a comprehensive package of benefits including paid time off (vacation, holidays, sick), medical/dental/vision insurance and 401(k) to eligible employees. This job is eligible to participate in our long-term incentive programs. Note: No amount of pay is considered to be wages or compensation until such amount is earned, vested, and determinable. The amount and availability of any bonus, commission, incentive, benefits, or any other form of compensation and benefits that are allocable to a particular employee remains in the Company's sole and absolute discretion unless and until paid and may be modified at the Company's sole and absolute discretion, consistent with applicable law. AbbVie is an equal opportunity employer and is committed to operating with integrity . click apply for full job details
About Us Visa is a world leader in payments technology, facilitating transactions between consumers, merchants, financial institutions and government entities across more than 200 countries and territories, dedicated to uplifting everyone, everywhere by being the best way to pay and be paid. At Visa, you'll have the opportunity to create impact at scale - tackling meaningful challenges, growing your skills and seeing your contributions impact lives around the world. Join Visa and do work that matters - to you, to your community, and to the world. Progress starts with you. Visa will accept applications for this role until at least 11-10-2026 Job Description The Opportunity We are seeking a talented and motivated Senior Software Development Engineer to join our Payments Products Development team. As a key member of the team, you will play a critical role in developing cutting-edge solutions, leveraging innovative technologies, and enhancing the capabilities of our platforms. You will quickly grasp and evaluate new ideas and technologies from internal and external sources, then match them to emerging technology and business opportunities while helping build a culture of innovation and engineering excellence. Essential Functions: AI-Enabled Innovative Development: Design, develop, and implement innovative software solutions using generative AI, conversational AI, RAG, and modern integration patterns. Explore new technologies and translate relevant ideas into secure, scalable business solutions. AI System Engineering: Design and integrate AI components into larger platforms, including data preparation, model evaluation, deployment, monitoring, and continuous improvement. Address robustness, quality, security, and operational reliability throughout the lifecycle. Collaborative Engineering: Collaborate with cross-functional teams to deliver complex projects that integrate emerging technologies with existing platforms. Work closely with Product Office, Operations & Infrastructure, Cybersecurity, Client Support, and Product Development teams. Continuous Learning: Actively expand knowledge of generative AI, machine learning, modern engineering practices, and emerging technologies. Share learning with peers and contribute to team growth. Client-Focused Solutions: Develop solutions with a client-centric mindset, ensuring Payment Product platforms deliver exceptional value and innovation. Use client feedback to refine and improve offerings. API and Integration Development: Contribute to the design and development of APIs that enhance integration across Payment Product applications, platforms, AI services, and solutions. Technology Modernization: Advance the modernization roadmap by adopting best-in-class technology solutions for core platforms, expanding market reach and client impact. Process Improvement: Continuously improve technology stacks, development processes, and methodologies to enhance productivity, quality, and time to market, including responsible use of AI-assisted engineering tools. Engineering Excellence: Follow industry best practices in software development, emphasizing quality, security, performance, scalability, availability, resilience, and reduction of technical debt. Automation and Best Practices: Automate software development, testing, deployment, and maintenance processes. Use AI-generated outputs as accelerators while applying rigorous engineering review and verification. Incident and Change Management: Support incident, change, and problem management processes. Participate in root-cause analysis and troubleshooting to sustain high availability and service reliability. Visa requires at least 3 days in office, expectations of these days will be confirmed by your Hiring Manager. Qualifications Basic Qualifications: 2+ years of relevant work experience and a Bachelors degree, OR 5+ years of relevant work experience Expert-level skills in Java, Python, and Node.js; experience with C++ or C# is a plus. Experience building Generative AI applications, conversational AI solutions, retrieval-augmented generation (RAG) architectures, and related techniques, tools, and libraries. Preferred Qualifications: 3 or more years of work experience with a Bachelor's Degree or more than 2 years of work experience with an Advanced Degree (e.g. Masters, MBA, JD, MD) Self-driven, adaptable, and willing to work across technologies and programming languages. Strong understanding of natural language processing concepts, including tokenization, word embeddings, and sequence models. Proficiency implementing and fine-tuning AI and machine learning models using frameworks such as TensorFlow, PyTorch, or scikit-learn. Understanding of machine learning and deep learning fundamentals, including neural network architectures, training procedures, transfer learning, model compression, and associated trade-offs. Ability to design, implement, and integrate AI components into larger enterprise systems. Familiarity with common robustness, reliability, security, and responsible-use considerations in AI systems. Experience working with large datasets, exploratory data analysis, data preprocessing, feature engineering, and model evaluation techniques. Exposure to leading-edge areas such as machine learning, deep learning, stream computing, MLOps, and modern AI integration patterns. Proficiency in front-end web development technologies such as React, Angular, and Node.js. Experience configuring build and deployment systems such as Docker, Jenkins, and Kubernetes. Expertise in multithreading, concurrency, and error handling. Demonstrated proficiency in troubleshooting, root-cause analysis, application design, and implementing enterprise-scale components. Knowledge of version control, CI/CD pipelines, and best practices for application and ML model deployment. Working knowledge of distributed in-memory computing technologies such as Redis. Understanding of enterprise security, certificate management, and related practices. Hands-on experience with Jenkins and container deployment architecture. Experience with OAuth 2.0, SSO, and authentication methods or protocols. Expertise in application security, SSDLC, and cryptography fundamentals. Experience applying AI-assisted engineering practices while independently validating generated code, tests, documentation, and technical recommendations. Experience in the payments technology industry is a plus. The Skills You Bring: Energy and Experience: A growth mindset, curiosity about technology, and enthusiasm for challenging projects on a global scale. Challenge the Status Quo: Comfort pushing boundaries and exploring solutions beyond traditional approaches. Language Expertise: Expertise in one or more development languages such as Java, Python, Node.js, C#, or C++. AI Builder: Experience building and deploying Generative AI, conversational AI, RAG, machine learning, modern services, and web applications with quality and scalability. Critical AI Judgment: Ability to evaluate AI-generated code and recommendations, identify failure modes, and apply independent engineering judgment. Learner: A consistent drive to learn technologies such as GenAI, machine learning, Angular, React, Kubernetes, and Docker. Partnership: Experience collaborating with Product, Test, DevOps, Cybersecurity, and Agile/Scrum teams. Information for US Applicants For roles located in the US, the estimated salary range for this position is $112,100 to $204,000 USD per year, which may include potential sales incentive payments (if applicable). Salary may vary depending on job-related factors which may include knowledge, skills, experience, and location. In addition, this position may be eligible for bonus and equity.Visa has a comprehensive benefits package for which this position may be eligible that includes Medical, Dental, Vision, 401(k), FSA/HSA, Life Insurance, Paid Time Off, and Wellness Program. Work Hours Varies upon the needs of the department. Travel Requirements This position requires travel 5-10% of the time. Mental/Physical Requirements This position will be performed in an office setting. The position will require the incumbent to sit and stand at a desk, communicate in person and by telephone, frequently operate standard office equipment, such as telephones and computers. Visa is an EEO Employer Qualified applicants will receive consideration for employment without regard to race, color religion, sex, national origin, sexual orientation, gender identity, disability or protect veteran status. Visa will also consider for employment qualified applicants with criminal histories in a manner consistent with the EEOC guidelines and applicable local law.
11/11/2026
Full time
About Us Visa is a world leader in payments technology, facilitating transactions between consumers, merchants, financial institutions and government entities across more than 200 countries and territories, dedicated to uplifting everyone, everywhere by being the best way to pay and be paid. At Visa, you'll have the opportunity to create impact at scale - tackling meaningful challenges, growing your skills and seeing your contributions impact lives around the world. Join Visa and do work that matters - to you, to your community, and to the world. Progress starts with you. Visa will accept applications for this role until at least 11-10-2026 Job Description The Opportunity We are seeking a talented and motivated Senior Software Development Engineer to join our Payments Products Development team. As a key member of the team, you will play a critical role in developing cutting-edge solutions, leveraging innovative technologies, and enhancing the capabilities of our platforms. You will quickly grasp and evaluate new ideas and technologies from internal and external sources, then match them to emerging technology and business opportunities while helping build a culture of innovation and engineering excellence. Essential Functions: AI-Enabled Innovative Development: Design, develop, and implement innovative software solutions using generative AI, conversational AI, RAG, and modern integration patterns. Explore new technologies and translate relevant ideas into secure, scalable business solutions. AI System Engineering: Design and integrate AI components into larger platforms, including data preparation, model evaluation, deployment, monitoring, and continuous improvement. Address robustness, quality, security, and operational reliability throughout the lifecycle. Collaborative Engineering: Collaborate with cross-functional teams to deliver complex projects that integrate emerging technologies with existing platforms. Work closely with Product Office, Operations & Infrastructure, Cybersecurity, Client Support, and Product Development teams. Continuous Learning: Actively expand knowledge of generative AI, machine learning, modern engineering practices, and emerging technologies. Share learning with peers and contribute to team growth. Client-Focused Solutions: Develop solutions with a client-centric mindset, ensuring Payment Product platforms deliver exceptional value and innovation. Use client feedback to refine and improve offerings. API and Integration Development: Contribute to the design and development of APIs that enhance integration across Payment Product applications, platforms, AI services, and solutions. Technology Modernization: Advance the modernization roadmap by adopting best-in-class technology solutions for core platforms, expanding market reach and client impact. Process Improvement: Continuously improve technology stacks, development processes, and methodologies to enhance productivity, quality, and time to market, including responsible use of AI-assisted engineering tools. Engineering Excellence: Follow industry best practices in software development, emphasizing quality, security, performance, scalability, availability, resilience, and reduction of technical debt. Automation and Best Practices: Automate software development, testing, deployment, and maintenance processes. Use AI-generated outputs as accelerators while applying rigorous engineering review and verification. Incident and Change Management: Support incident, change, and problem management processes. Participate in root-cause analysis and troubleshooting to sustain high availability and service reliability. Visa requires at least 3 days in office, expectations of these days will be confirmed by your Hiring Manager. Qualifications Basic Qualifications: 2+ years of relevant work experience and a Bachelors degree, OR 5+ years of relevant work experience Expert-level skills in Java, Python, and Node.js; experience with C++ or C# is a plus. Experience building Generative AI applications, conversational AI solutions, retrieval-augmented generation (RAG) architectures, and related techniques, tools, and libraries. Preferred Qualifications: 3 or more years of work experience with a Bachelor's Degree or more than 2 years of work experience with an Advanced Degree (e.g. Masters, MBA, JD, MD) Self-driven, adaptable, and willing to work across technologies and programming languages. Strong understanding of natural language processing concepts, including tokenization, word embeddings, and sequence models. Proficiency implementing and fine-tuning AI and machine learning models using frameworks such as TensorFlow, PyTorch, or scikit-learn. Understanding of machine learning and deep learning fundamentals, including neural network architectures, training procedures, transfer learning, model compression, and associated trade-offs. Ability to design, implement, and integrate AI components into larger enterprise systems. Familiarity with common robustness, reliability, security, and responsible-use considerations in AI systems. Experience working with large datasets, exploratory data analysis, data preprocessing, feature engineering, and model evaluation techniques. Exposure to leading-edge areas such as machine learning, deep learning, stream computing, MLOps, and modern AI integration patterns. Proficiency in front-end web development technologies such as React, Angular, and Node.js. Experience configuring build and deployment systems such as Docker, Jenkins, and Kubernetes. Expertise in multithreading, concurrency, and error handling. Demonstrated proficiency in troubleshooting, root-cause analysis, application design, and implementing enterprise-scale components. Knowledge of version control, CI/CD pipelines, and best practices for application and ML model deployment. Working knowledge of distributed in-memory computing technologies such as Redis. Understanding of enterprise security, certificate management, and related practices. Hands-on experience with Jenkins and container deployment architecture. Experience with OAuth 2.0, SSO, and authentication methods or protocols. Expertise in application security, SSDLC, and cryptography fundamentals. Experience applying AI-assisted engineering practices while independently validating generated code, tests, documentation, and technical recommendations. Experience in the payments technology industry is a plus. The Skills You Bring: Energy and Experience: A growth mindset, curiosity about technology, and enthusiasm for challenging projects on a global scale. Challenge the Status Quo: Comfort pushing boundaries and exploring solutions beyond traditional approaches. Language Expertise: Expertise in one or more development languages such as Java, Python, Node.js, C#, or C++. AI Builder: Experience building and deploying Generative AI, conversational AI, RAG, machine learning, modern services, and web applications with quality and scalability. Critical AI Judgment: Ability to evaluate AI-generated code and recommendations, identify failure modes, and apply independent engineering judgment. Learner: A consistent drive to learn technologies such as GenAI, machine learning, Angular, React, Kubernetes, and Docker. Partnership: Experience collaborating with Product, Test, DevOps, Cybersecurity, and Agile/Scrum teams. Information for US Applicants For roles located in the US, the estimated salary range for this position is $112,100 to $204,000 USD per year, which may include potential sales incentive payments (if applicable). Salary may vary depending on job-related factors which may include knowledge, skills, experience, and location. In addition, this position may be eligible for bonus and equity.Visa has a comprehensive benefits package for which this position may be eligible that includes Medical, Dental, Vision, 401(k), FSA/HSA, Life Insurance, Paid Time Off, and Wellness Program. Work Hours Varies upon the needs of the department. Travel Requirements This position requires travel 5-10% of the time. Mental/Physical Requirements This position will be performed in an office setting. The position will require the incumbent to sit and stand at a desk, communicate in person and by telephone, frequently operate standard office equipment, such as telephones and computers. Visa is an EEO Employer Qualified applicants will receive consideration for employment without regard to race, color religion, sex, national origin, sexual orientation, gender identity, disability or protect veteran status. Visa will also consider for employment qualified applicants with criminal histories in a manner consistent with the EEOC guidelines and applicable local law.
Job Description Job Description Company Description About AbbVie AbbVie's mission is to discover and deliver innovative medicines and solutions that solve serious health issues today and address the medical challenges of tomorrow. We strive to have a remarkable impact on people's lives across several key therapeutic areas including immunology, oncology and neuroscience - and products and services in our Allergan Aesthetics portfolio. For more information about AbbVie, please visit us at . on LinkedIn, Facebook, Instagram, X and YouTube. Job Description As a discipline expert and technology leader, the Principal AI Engineer II will define and advance the strategy, architecture, and engineering practices required to develop, deploy, and scale artificial intelligence solutions across AbbVie. This role will investigate, identify, and implement state-of-the-art technology platforms that drive productivity and efficiency gains in own function and throughout multiple business areas. Technical leader acting at a group, department, and cross-functional levels. Responsible for managing the Data, Solutions, Business, and/or technology environments and tying them to the Enterprise Architecture and other architectures designs. Responsibilities: Define and advance AI engineering strategy, architecture, standards, and roadmaps aligned with AbbVie's business and technology objectives. Architect and build secure, scalable, reusable AI platforms, services, developer tools, and components that support enterprise adoption. Lead production-grade AI solutions from ideation and prototyping through development, testing, validation, deployment, monitoring, continuous improvement, and retirement. Integrate AI platforms with AWS services and enterprise data, software, security, identity, and infrastructure environments. Establish practices for evaluation, testing, versioning, release management, observability, performance monitoring, incident response, and operational support. Apply risk-based approaches to compliance, GxP, data integrity, privacy, cybersecurity, documentation, traceability, human oversight, and responsible AI. Partner with Quality, Regulatory, Legal, Privacy, Information Security, scientific, technical, and business stakeholders to deliver fit-for-purpose solutions. Serve as a trusted technical advisor, facilitate alignment, influence decisions without direct authority, and communicate complex tradeoffs and recommendations to technical and non-technical audiences. Evaluate emerging technologies, lead innovation and proof-of-concept efforts, and guide promising solutions into sustainable production capabilities. Mentor engineers, advance engineering maturity, promote knowledge sharing, and represent AbbVie in relevant technical communities and partner engagements. Qualifications Required Bachelor's degree with 9 years' experience, Master's degree with 8 years' experience, or PhD with 4 years' in Computer Science, Artificial Intelligence, Machine Learning, Data Science, Engineering, or a related technical discipline. Demonstrated experience designing, deploying, and operating production-scale AI and machine learning systems. Strong experience in AI/platform engineering, including scalable platforms, reusable components, and production-grade AI solutions. Demonstrated experience designing, building, deploying, and supporting solutions using AWS systems and services. Strong software and cloud engineering practices, including secure design, automated testing, CI/CD, containerization, monitoring, and operational support. Experience working in a regulated environment, preferably pharmaceutical, biotechnology, healthcare, medical device, or life sciences. Experience supporting the full solution lifecycle, including feasibility, design, development, testing, validation, deployment, and ongoing operations. Strong understanding of risk management, validation, change control, data integrity, cybersecurity, privacy, documentation, and quality requirements. Demonstrated ability to manage complex stakeholders, influence technical and business decisions, and collaborate across organizational boundaries. Excellent communication skills with senior leaders, technical teams, scientific experts, business partners, and external collaborators. Demonstrated innovation and mentoring experience, including advancing engineering practices and delivering measurable impact. Preferred Experience with enterprise AI governance, responsible AI, model validation, human oversight, and AI lifecycle management. Experience with MLOps and production engineering, including model evaluation, APIs, microservices, CI/CD, observability, and infrastructure as code. Open-source contributions or technical thought leadership through publications, patents, or industry working groups. Experience leading cross-functional product development from feasibility through validation and production implementation. Enterprise AI or platform experience, including AWS architecture, governance, security, and integration with enterprise environments. Additional Information Applicable only to applicants applying to a position in any location with pay disclosure requirements under state or local law: The compensation range described below is the range of possible base pay compensation that the Company believes in good faith it will pay for this role at the time of this posting based on the job grade for this position. Individual compensation paid within this range will depend on many factors including geographic location, and we may ultimately pay more or less than the posted range. This range may be modified in the future. We offer a comprehensive package of benefits including paid time off (vacation, holidays, sick), medical/dental/vision insurance and 401(k) to eligible employees. This job is eligible to participate in our long-term incentive programs. Note: No amount of pay is considered to be wages or compensation until such amount is earned, vested, and determinable. The amount and availability of any bonus, commission, incentive, benefits, or any other form of compensation and benefits that are allocable to a particular employee remains in the Company's sole and absolute discretion unless and until paid and may be modified at the Company's sole and absolute discretion, consistent with applicable law. AbbVie is an equal opportunity employer and is committed to operating with integrity, driving innovation, transforming lives and serving our community. Equal Opportunity Employer/Veterans/Disabled. US & Puerto Rico only - to learn more, visit -us/equal-employment-opportunity-employer.html US & Puerto Rico applicants seeking a reasonable accommodation, click here to learn more: -us/reasonable- accommodations.html
09/28/2026
Full time
Job Description Job Description Company Description About AbbVie AbbVie's mission is to discover and deliver innovative medicines and solutions that solve serious health issues today and address the medical challenges of tomorrow. We strive to have a remarkable impact on people's lives across several key therapeutic areas including immunology, oncology and neuroscience - and products and services in our Allergan Aesthetics portfolio. For more information about AbbVie, please visit us at . on LinkedIn, Facebook, Instagram, X and YouTube. Job Description As a discipline expert and technology leader, the Principal AI Engineer II will define and advance the strategy, architecture, and engineering practices required to develop, deploy, and scale artificial intelligence solutions across AbbVie. This role will investigate, identify, and implement state-of-the-art technology platforms that drive productivity and efficiency gains in own function and throughout multiple business areas. Technical leader acting at a group, department, and cross-functional levels. Responsible for managing the Data, Solutions, Business, and/or technology environments and tying them to the Enterprise Architecture and other architectures designs. Responsibilities: Define and advance AI engineering strategy, architecture, standards, and roadmaps aligned with AbbVie's business and technology objectives. Architect and build secure, scalable, reusable AI platforms, services, developer tools, and components that support enterprise adoption. Lead production-grade AI solutions from ideation and prototyping through development, testing, validation, deployment, monitoring, continuous improvement, and retirement. Integrate AI platforms with AWS services and enterprise data, software, security, identity, and infrastructure environments. Establish practices for evaluation, testing, versioning, release management, observability, performance monitoring, incident response, and operational support. Apply risk-based approaches to compliance, GxP, data integrity, privacy, cybersecurity, documentation, traceability, human oversight, and responsible AI. Partner with Quality, Regulatory, Legal, Privacy, Information Security, scientific, technical, and business stakeholders to deliver fit-for-purpose solutions. Serve as a trusted technical advisor, facilitate alignment, influence decisions without direct authority, and communicate complex tradeoffs and recommendations to technical and non-technical audiences. Evaluate emerging technologies, lead innovation and proof-of-concept efforts, and guide promising solutions into sustainable production capabilities. Mentor engineers, advance engineering maturity, promote knowledge sharing, and represent AbbVie in relevant technical communities and partner engagements. Qualifications Required Bachelor's degree with 9 years' experience, Master's degree with 8 years' experience, or PhD with 4 years' in Computer Science, Artificial Intelligence, Machine Learning, Data Science, Engineering, or a related technical discipline. Demonstrated experience designing, deploying, and operating production-scale AI and machine learning systems. Strong experience in AI/platform engineering, including scalable platforms, reusable components, and production-grade AI solutions. Demonstrated experience designing, building, deploying, and supporting solutions using AWS systems and services. Strong software and cloud engineering practices, including secure design, automated testing, CI/CD, containerization, monitoring, and operational support. Experience working in a regulated environment, preferably pharmaceutical, biotechnology, healthcare, medical device, or life sciences. Experience supporting the full solution lifecycle, including feasibility, design, development, testing, validation, deployment, and ongoing operations. Strong understanding of risk management, validation, change control, data integrity, cybersecurity, privacy, documentation, and quality requirements. Demonstrated ability to manage complex stakeholders, influence technical and business decisions, and collaborate across organizational boundaries. Excellent communication skills with senior leaders, technical teams, scientific experts, business partners, and external collaborators. Demonstrated innovation and mentoring experience, including advancing engineering practices and delivering measurable impact. Preferred Experience with enterprise AI governance, responsible AI, model validation, human oversight, and AI lifecycle management. Experience with MLOps and production engineering, including model evaluation, APIs, microservices, CI/CD, observability, and infrastructure as code. Open-source contributions or technical thought leadership through publications, patents, or industry working groups. Experience leading cross-functional product development from feasibility through validation and production implementation. Enterprise AI or platform experience, including AWS architecture, governance, security, and integration with enterprise environments. Additional Information Applicable only to applicants applying to a position in any location with pay disclosure requirements under state or local law: The compensation range described below is the range of possible base pay compensation that the Company believes in good faith it will pay for this role at the time of this posting based on the job grade for this position. Individual compensation paid within this range will depend on many factors including geographic location, and we may ultimately pay more or less than the posted range. This range may be modified in the future. We offer a comprehensive package of benefits including paid time off (vacation, holidays, sick), medical/dental/vision insurance and 401(k) to eligible employees. This job is eligible to participate in our long-term incentive programs. Note: No amount of pay is considered to be wages or compensation until such amount is earned, vested, and determinable. The amount and availability of any bonus, commission, incentive, benefits, or any other form of compensation and benefits that are allocable to a particular employee remains in the Company's sole and absolute discretion unless and until paid and may be modified at the Company's sole and absolute discretion, consistent with applicable law. AbbVie is an equal opportunity employer and is committed to operating with integrity, driving innovation, transforming lives and serving our community. Equal Opportunity Employer/Veterans/Disabled. US & Puerto Rico only - to learn more, visit -us/equal-employment-opportunity-employer.html US & Puerto Rico applicants seeking a reasonable accommodation, click here to learn more: -us/reasonable- accommodations.html