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Senior Automation Engineer
Danaher Logan, Utah
This job is with Danaher, an inclusive employer and a member of myGwork - the largest global platform for the LGBTQ+ business community. Please do not contact the recruiter directly. Bring more to life. Are you ready to accelerate your potential and make a real difference within life sciences, diagnostics and biotechnology? At Cytiva, one of Danaher's 15+ operating companies, our work saves lives-and we're all united by a shared commitment to innovate for tangible impact. You'll thrive in a culture of belonging where you and your unique viewpoint matter. And by harnessing Danaher's system of continuous improvement, you help turn ideas into impact - innovating at the speed of life. Working at Cytiva means being at the forefront of providing new solutions to transform human health. Our incredible customers undertake life-saving activities ranging from fundamental biological research to developing innovative vaccines, new medicines, and cell and gene therapies. At Cytiva you will be able to continuously improve yourself and us - working on challenges that truly matter with people that care for each other, our customers, and their patients. Take your next step to an altogether life-changing career. Learn about the Danaher Business System which makes everything possible. Senior Automation Engineer The Senior Automation Engineer is responsible for leading the design, implementation, optimization, and lifecycle support of manufacturing automation and control systems across the Logan site. This role drives automation strategy, capital project execution, equipment reliability improvements, and technical standardization while partnering with Manufacturing, Quality, Maintenance, EHS, and Engineering teams to support operational excellence and business growth. This position reports to the Sr. Project & Automation Manager and is part of the Project & Automation Engineering team located in Logan, Utah and will be an on-site role . What you will do: Lead the design, implementation, commissioning, and lifecycle management of PLC, HMI, SCADA, instrumentation, and industrial networking systems supporting manufacturing operations. Serve as the controls & automation engineering lead for capital projects, including automation architecture, vendor management, FAT/SAT execution, startup, and operational handoff. Develop and maintain site automation standards, cybersecurity practices, documentation standards, and equipment modernization roadmaps. Lead complex troubleshooting and root cause analysis for critical manufacturing systems to improve reliability, OEE, and process performance. Provide technical leadership and mentorship for automation and controls activities across the site, influencing engineering best practices, developing internal capabilities, and driving adoption of emerging automation technologies. Who you are: Bachelor's degree in Automation, Controls, Mechatronics, Electrical, Computer Engineering, or a related technical discipline, with 10+ years of industrial automation and controls engineering experience in a manufacturing environment; equivalent combinations of education, technical training, certifications, and directly related experience will also be considered. Demonstrated success leading automation scope for capital projects from concept through startup, including system design, vendor management, commissioning, and operational handoff. Expert-level experience programming and troubleshooting PLC and HMI platforms such as Rockwell Automation Studio 5000 and FactoryTalk View. Deep technical expertise with industrial control systems, instrumentation, electrical systems, and industrial communication networks. Travel, Motor Vehicle Record & Physical/Environment Requirements: Ability to travel up to 15% to support vendors, training, and other Cytiva facilities. Ability to work in manufacturing, utility, and laboratory environments. Ability to stand, walk, climb stairs, and occasionally lift up to 25 pounds. It would be a plus if you also possess previous experience in: Life sciences, biotechnology, pharmaceutical, or medical device manufacturing. Ignition, Manufacturing Execution Systems (MES), data historians, or ISA-88/ISA-95 automation frameworks. Commissioning, qualification, and validation of regulated manufacturing systems. Cytiva, a Danaher operating company, offers a broad array of comprehensive, competitive benefit programs that add value to our lives. Whether it's a health care program or paid time off, our programs contribute to life beyond the job. Check out our benefits at Danaher Benefits Info . This job is also eligible for bonus/incentive pay. Join our winning team today. Together, we'll accelerate the real-life impact of tomorrow's science and technology. We partner with customers across the globe to help them solve their most complex challenges, architecting solutions that bring the power of science to life. For more information, visit . Danaher Corporation and all Danaher Companies are committed to equal opportunity regardless of race, color, national origin, religion, sex, age, marital status, disability, veteran status, sexual orientation, gender identity, or other characteristics protected by law. The U.S. EEO posters are available here . For candidates who are based outside of New York City or who are applying for roles outside of New York City, for more information about conditions of any job offer please click here . We comply with federal and state disability laws and make reasonable accommodations for applicants and employees with disabilities. If reasonable accommodation is needed to participate in the job application or interview process, to perform essential job functions, and/or to receive other benefits and privileges of employment, please contact:1- or .
11/14/2026
Full time
This job is with Danaher, an inclusive employer and a member of myGwork - the largest global platform for the LGBTQ+ business community. Please do not contact the recruiter directly. Bring more to life. Are you ready to accelerate your potential and make a real difference within life sciences, diagnostics and biotechnology? At Cytiva, one of Danaher's 15+ operating companies, our work saves lives-and we're all united by a shared commitment to innovate for tangible impact. You'll thrive in a culture of belonging where you and your unique viewpoint matter. And by harnessing Danaher's system of continuous improvement, you help turn ideas into impact - innovating at the speed of life. Working at Cytiva means being at the forefront of providing new solutions to transform human health. Our incredible customers undertake life-saving activities ranging from fundamental biological research to developing innovative vaccines, new medicines, and cell and gene therapies. At Cytiva you will be able to continuously improve yourself and us - working on challenges that truly matter with people that care for each other, our customers, and their patients. Take your next step to an altogether life-changing career. Learn about the Danaher Business System which makes everything possible. Senior Automation Engineer The Senior Automation Engineer is responsible for leading the design, implementation, optimization, and lifecycle support of manufacturing automation and control systems across the Logan site. This role drives automation strategy, capital project execution, equipment reliability improvements, and technical standardization while partnering with Manufacturing, Quality, Maintenance, EHS, and Engineering teams to support operational excellence and business growth. This position reports to the Sr. Project & Automation Manager and is part of the Project & Automation Engineering team located in Logan, Utah and will be an on-site role . What you will do: Lead the design, implementation, commissioning, and lifecycle management of PLC, HMI, SCADA, instrumentation, and industrial networking systems supporting manufacturing operations. Serve as the controls & automation engineering lead for capital projects, including automation architecture, vendor management, FAT/SAT execution, startup, and operational handoff. Develop and maintain site automation standards, cybersecurity practices, documentation standards, and equipment modernization roadmaps. Lead complex troubleshooting and root cause analysis for critical manufacturing systems to improve reliability, OEE, and process performance. Provide technical leadership and mentorship for automation and controls activities across the site, influencing engineering best practices, developing internal capabilities, and driving adoption of emerging automation technologies. Who you are: Bachelor's degree in Automation, Controls, Mechatronics, Electrical, Computer Engineering, or a related technical discipline, with 10+ years of industrial automation and controls engineering experience in a manufacturing environment; equivalent combinations of education, technical training, certifications, and directly related experience will also be considered. Demonstrated success leading automation scope for capital projects from concept through startup, including system design, vendor management, commissioning, and operational handoff. Expert-level experience programming and troubleshooting PLC and HMI platforms such as Rockwell Automation Studio 5000 and FactoryTalk View. Deep technical expertise with industrial control systems, instrumentation, electrical systems, and industrial communication networks. Travel, Motor Vehicle Record & Physical/Environment Requirements: Ability to travel up to 15% to support vendors, training, and other Cytiva facilities. Ability to work in manufacturing, utility, and laboratory environments. Ability to stand, walk, climb stairs, and occasionally lift up to 25 pounds. It would be a plus if you also possess previous experience in: Life sciences, biotechnology, pharmaceutical, or medical device manufacturing. Ignition, Manufacturing Execution Systems (MES), data historians, or ISA-88/ISA-95 automation frameworks. Commissioning, qualification, and validation of regulated manufacturing systems. Cytiva, a Danaher operating company, offers a broad array of comprehensive, competitive benefit programs that add value to our lives. Whether it's a health care program or paid time off, our programs contribute to life beyond the job. Check out our benefits at Danaher Benefits Info . This job is also eligible for bonus/incentive pay. Join our winning team today. Together, we'll accelerate the real-life impact of tomorrow's science and technology. We partner with customers across the globe to help them solve their most complex challenges, architecting solutions that bring the power of science to life. For more information, visit . Danaher Corporation and all Danaher Companies are committed to equal opportunity regardless of race, color, national origin, religion, sex, age, marital status, disability, veteran status, sexual orientation, gender identity, or other characteristics protected by law. The U.S. EEO posters are available here . For candidates who are based outside of New York City or who are applying for roles outside of New York City, for more information about conditions of any job offer please click here . We comply with federal and state disability laws and make reasonable accommodations for applicants and employees with disabilities. If reasonable accommodation is needed to participate in the job application or interview process, to perform essential job functions, and/or to receive other benefits and privileges of employment, please contact:1- or .
Principal Data Scientist
AbbVie Irvine, California
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
Principal Data Scientist
AbbVie Lake Forest, Illinois
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
CSL Behring
Senior Software Engineer - Pharmaceutical R&D Systems
CSL Behring King Of Prussia, Pennsylvania
CSL Behring seeks a Senior Programmer to build secure, scalable applications that power pharmaceutical R&D and data management. In this role, you will design and implement enterprise software, integrate scientific and clinical systems, and ensure compliance with GxP and data integrity standards. Collaborating closely with researchers and IT teams, you'll translate complex requirements into robust, high-quality code. CSL offers a collaborative, inclusive culture with strong focus on learning, patient impact, and continuous professional development in a cutting-edge biotech environment. Responsibilities Design, develop, and maintain enterprise software supporting pharmaceutical R&D and data management Collaborate with scientists, data managers, and IT teams to translate requirements into robust technical solutions Ensure systems comply with Gx P, data integrity, and security standards Optimize application performance, reliability, and scalability in a regulated environment Mentor junior developers and contribute to code reviews and best practices Integrate laboratory, clinical, and business systems via APIs and data pipelines Participate in Agile ceremonies and drive continuous improvement Document technical designs, validation evidence, and operational procedures Troubleshoot complex production issues and implement sustainable fixes Partner with stakeholders to evaluate new technologies and tools Required Skills Java or C# programming Python scripting SQL and relational databases Cloud platforms (AWS/Azure/GCP) RESTful API design and integration Source control (Git) Agile/Scrum methodologies Data integration and ETL tools Pharmaceutical Gx P/21 CFR Part 11 compliance System design and architecture
09/30/2026
Full time
CSL Behring seeks a Senior Programmer to build secure, scalable applications that power pharmaceutical R&D and data management. In this role, you will design and implement enterprise software, integrate scientific and clinical systems, and ensure compliance with GxP and data integrity standards. Collaborating closely with researchers and IT teams, you'll translate complex requirements into robust, high-quality code. CSL offers a collaborative, inclusive culture with strong focus on learning, patient impact, and continuous professional development in a cutting-edge biotech environment. Responsibilities Design, develop, and maintain enterprise software supporting pharmaceutical R&D and data management Collaborate with scientists, data managers, and IT teams to translate requirements into robust technical solutions Ensure systems comply with Gx P, data integrity, and security standards Optimize application performance, reliability, and scalability in a regulated environment Mentor junior developers and contribute to code reviews and best practices Integrate laboratory, clinical, and business systems via APIs and data pipelines Participate in Agile ceremonies and drive continuous improvement Document technical designs, validation evidence, and operational procedures Troubleshoot complex production issues and implement sustainable fixes Partner with stakeholders to evaluate new technologies and tools Required Skills Java or C# programming Python scripting SQL and relational databases Cloud platforms (AWS/Azure/GCP) RESTful API design and integration Source control (Git) Agile/Scrum methodologies Data integration and ETL tools Pharmaceutical Gx P/21 CFR Part 11 compliance System design and architecture
Principal AI Engineer II
AbbVie North Chicago, Illinois
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

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