Sentara Health
Virginia Beach, Virginia
City/State Virginia Beach, VA Work Shift First (Days) Overview: Sentara is hiring for a Senior Data Scientist! This position is fully remote. Overview We are seeking a highly skilled and experienced Data Science ML Operations and Gen AI Engineer (or Senior) to join us and help advance our current and future work applying machine learning, deep learning, and NLP to deliver better healthcare. The Senior Data Scientist will leverage data to improve healthcare outcomes and drive data-driven decision-making. Leveraging expertise in statistical analysis and machine learning, this role will collaborate with cross-functional teams to solve complex healthcare challenges and enhance patient care. This role will directly contribute to advancing medical research, optimizing healthcare processes, and delivering innovative solutions in the healthcare industry. As a Senior ML Engineer on our team, you will play a crucial role in identifying gaps in our existing ML platform and architecting and building solutions to address those gaps. You will also collaborate with the AI team's ML Scientists and our partner data engineering and software development teams to bring ML AND Gen AI models to production and maintain their health and integrity while in production. Your expertise in machine learning and Gen AI, coupled with a strong background in software development, will be instrumental in driving the success of Sentara's AI/ML initiatives. Qualifications: • 5+ years building production software/ML systems, including 1+ years of experience with LLMs/GenAI. • Proficient in Python and one major DL/LLM stack (e.g., PyTorch/Transformers); experience with LangChain/LlamaIndex, vector DBs, and cloud (AWS/Azure/GCP). • Demonstrated delivery of RAG, prompt engineering, evaluation frameworks, and guardrails in production. • Strength in APIs, distributed systems, and ML Ops (K8s, CI/CD, monitoring). • Experience with EPIC health platform is highly preferred • Experience with ML platforms and ML Ops: Demonstrated experience in assessing and improving ML platforms, identifying gaps, and architecting solutions to address them. Strong familiarity with ML platform components such as data ingestion, preprocessing, feature stores, model training, deployment, and monitoring. • Experience with SQL and big data platforms such as Postgres, Redshift and Snowflake • Experience with Agile/Scrum methodology and best practices Preferred: • Previous work experience with Generative AI and ML Ops in healthcare EPIC environment • Understanding of use and implementation of Vector Databases • Kubernetes container orchestration experience Responsibilities • Responsible for design and development of production-grade Machine Learning ops and Gen AI solutions • Lead hands-on delivery of scalable GenAI solutions from problem framing prototyping evaluation production monitoring. • Build internal copilots/assistants (knowledge search, code/content generation) and client-facing products (conversational analytics, summarization, recommendations, workflow automation). • Design RAG pipelines, embedding strategies, vector search, and model orchestration; evaluate fine-tuning vs. prompt engineering. • Implement guardrails, safety filters, prompt/version management, latency/throughput optimizations, and cost controls. • ML platform and ML Ops: Identify areas that require improvements or additional functionalities and use your expertise in machine learning and software engineering to architect and develop solutions that fill gaps in our ML platform and development ecosystem. Analyze system performance, scalability, and reliability to pinpoint opportunities for enhancement. Develop tools and solutions that help the team build, deploy, and monitor AI/ML solutions efficiently. • System scalability and reliability: Optimize the scalability, performance, and reliability and AI Team solutions by implementing best practices and leveraging industry-standard technologies. Collaborate with infrastructure teams to ensure smooth integration and deployment of ML solutions. Design scalable and efficient systems that leverage the power of machine learning for enhanced performance and capabilities. • Data processing and workflow pipelines: Streamline data ingestion, preprocessing, feature engineering, and model training workflows to improve efficiency and reduce latency. Work with data engineering and data platform teams to design and implement robust data pipelines that support the AI team's needs. • Model deployment and monitoring: Evaluate and optimize model prototypes for real-world performance. Work with infrastructure and development teams to integrate ML models into production systems. Work closely with partner teams to communicate and understand technical requirements and challenges. • As part of Sentara's Data Science team you will be responsible for implementation and operationalization of AI/ML models. You will work with other machine learning engineers, data scientists, software engineers and platform engineers to ensure success of the AI/ML implementations. Specific responsibilities will include: • Apply software engineering rigor and best practices to machine learning, including AI/MLOPs, CI/CD, automation, etc. • Take offline models data scientists build and turn them into a real machine learning production system. Education Bachelor's Degree (Required) Certification/Licensure No specific certification or licensure requirements Experience Required to have 5+ years of experience as a Data Scientist with a strong focus on Azure and Microsoft Data Science, AI, and machine learning toolsets. Required to have strong problem-solving skills and the ability to tackle complex healthcare challenges using data-driven approaches. Can help the Data Science infrastructure building up, working with ML Ops team for model implementation, mentoring and developing junior staff. Required to have s trong proficiency in data analysis, data manipulation, and data visualization using Python. Required to have f amiliarity with healthcare-related datasets, medical terminologies, and electronic health records (EHR) data. Required to have knowledge of statistical techniques, hypothesis testing, and experimental design for healthcare research. Required to have s trong machine learning expertise: Proficient in machine learning algorithms, statistical modeling, and data analysis. Hands-on experience with standard ML frameworks (e.g., TensorFlow, PyTorch) and libraries (e.g., scikit-learn, XGBoost, TensorFlow, or Keras). Required to have solid understanding of data engineering principles, data structures, and algorithms. Proficient in Python and/or other programming languages commonly used in ML development. Required to have experience in technologies, frameworks and architecture like Java or Python, Angular, React, JSON, Application Servers, CI/CD is preferred. Required to have experience with one or more AI automations platforms like Kubeflow pipeline, MLFlow, Azure Pipeline, AWS Sage Maker Pipeline, Airflow, Jenkins, Spark, Hadoop, Kafka, Jira and GIT. We provide market-competitive compensation packages, inclusive of base pay, incentives, and benefits. The base pay rate for full-time employment is: $91,416.00 - $152,380.80. Additional compensation may be available for this role such as shift differentials, standby/on-call, overtime, premiums, extra shift incentives, or bonus opportunities. Benefits: Caring For Your Family and Your Career • Medical, Dental, Vision plans • Adoption, Fertility and Surrogacy Reimbursement up to $10,000 • Paid Time Off and Sick Leave • Paid Parental & Family Caregiver Leave • Emergency Backup Care • Long-Term, Short-Term Disability, and Critical Illness plans • Life Insurance • 401k/403B with Employer Match • Tuition Assistance - $5,250/year and discounted educational opportunities through Guild Education • Student Debt Pay Down - $10,000 • Reimbursement for certifications and free access to complete CEUs and professional development •Pet Insurance •Legal Resources Plan •Colleagues have the opportunity to earn an annual discretionary bonus ifestablished system and employee eligibility criteria is met. Sentara Health is an equal opportunity employer and prides itself on the diversity and inclusiveness of its close to an almost 30,000-member workforce. Diversity, inclusion, and belonging is a guiding principle of the organization to ensure its workforce reflects the communities it serves. In support of our mission "to improve health every day," this is a tobacco-free environment. For positions that are available as remote work, Sentara Health employs associates in the following states: Alabama, Delaware, Florida, Georgia, Idaho, Indiana, Kansas, Louisiana, Maine, Maryland, Minnesota, Nebraska, Nevada, New Hampshire, North Carolina, North Dakota, Ohio, Oklahoma, Pennsylvania, South Carolina, South Dakota, Tennessee, Texas, Utah, Virginia, Washington, West Virginia, Wisconsin, and Wyoming.
City/State Virginia Beach, VA Work Shift First (Days) Overview: Sentara is hiring for a Senior Data Scientist! This position is fully remote. Overview We are seeking a highly skilled and experienced Data Science ML Operations and Gen AI Engineer (or Senior) to join us and help advance our current and future work applying machine learning, deep learning, and NLP to deliver better healthcare. The Senior Data Scientist will leverage data to improve healthcare outcomes and drive data-driven decision-making. Leveraging expertise in statistical analysis and machine learning, this role will collaborate with cross-functional teams to solve complex healthcare challenges and enhance patient care. This role will directly contribute to advancing medical research, optimizing healthcare processes, and delivering innovative solutions in the healthcare industry. As a Senior ML Engineer on our team, you will play a crucial role in identifying gaps in our existing ML platform and architecting and building solutions to address those gaps. You will also collaborate with the AI team's ML Scientists and our partner data engineering and software development teams to bring ML AND Gen AI models to production and maintain their health and integrity while in production. Your expertise in machine learning and Gen AI, coupled with a strong background in software development, will be instrumental in driving the success of Sentara's AI/ML initiatives. Qualifications: • 5+ years building production software/ML systems, including 1+ years of experience with LLMs/GenAI. • Proficient in Python and one major DL/LLM stack (e.g., PyTorch/Transformers); experience with LangChain/LlamaIndex, vector DBs, and cloud (AWS/Azure/GCP). • Demonstrated delivery of RAG, prompt engineering, evaluation frameworks, and guardrails in production. • Strength in APIs, distributed systems, and ML Ops (K8s, CI/CD, monitoring). • Experience with EPIC health platform is highly preferred • Experience with ML platforms and ML Ops: Demonstrated experience in assessing and improving ML platforms, identifying gaps, and architecting solutions to address them. Strong familiarity with ML platform components such as data ingestion, preprocessing, feature stores, model training, deployment, and monitoring. • Experience with SQL and big data platforms such as Postgres, Redshift and Snowflake • Experience with Agile/Scrum methodology and best practices Preferred: • Previous work experience with Generative AI and ML Ops in healthcare EPIC environment • Understanding of use and implementation of Vector Databases • Kubernetes container orchestration experience Responsibilities • Responsible for design and development of production-grade Machine Learning ops and Gen AI solutions • Lead hands-on delivery of scalable GenAI solutions from problem framing prototyping evaluation production monitoring. • Build internal copilots/assistants (knowledge search, code/content generation) and client-facing products (conversational analytics, summarization, recommendations, workflow automation). • Design RAG pipelines, embedding strategies, vector search, and model orchestration; evaluate fine-tuning vs. prompt engineering. • Implement guardrails, safety filters, prompt/version management, latency/throughput optimizations, and cost controls. • ML platform and ML Ops: Identify areas that require improvements or additional functionalities and use your expertise in machine learning and software engineering to architect and develop solutions that fill gaps in our ML platform and development ecosystem. Analyze system performance, scalability, and reliability to pinpoint opportunities for enhancement. Develop tools and solutions that help the team build, deploy, and monitor AI/ML solutions efficiently. • System scalability and reliability: Optimize the scalability, performance, and reliability and AI Team solutions by implementing best practices and leveraging industry-standard technologies. Collaborate with infrastructure teams to ensure smooth integration and deployment of ML solutions. Design scalable and efficient systems that leverage the power of machine learning for enhanced performance and capabilities. • Data processing and workflow pipelines: Streamline data ingestion, preprocessing, feature engineering, and model training workflows to improve efficiency and reduce latency. Work with data engineering and data platform teams to design and implement robust data pipelines that support the AI team's needs. • Model deployment and monitoring: Evaluate and optimize model prototypes for real-world performance. Work with infrastructure and development teams to integrate ML models into production systems. Work closely with partner teams to communicate and understand technical requirements and challenges. • As part of Sentara's Data Science team you will be responsible for implementation and operationalization of AI/ML models. You will work with other machine learning engineers, data scientists, software engineers and platform engineers to ensure success of the AI/ML implementations. Specific responsibilities will include: • Apply software engineering rigor and best practices to machine learning, including AI/MLOPs, CI/CD, automation, etc. • Take offline models data scientists build and turn them into a real machine learning production system. Education Bachelor's Degree (Required) Certification/Licensure No specific certification or licensure requirements Experience Required to have 5+ years of experience as a Data Scientist with a strong focus on Azure and Microsoft Data Science, AI, and machine learning toolsets. Required to have strong problem-solving skills and the ability to tackle complex healthcare challenges using data-driven approaches. Can help the Data Science infrastructure building up, working with ML Ops team for model implementation, mentoring and developing junior staff. Required to have s trong proficiency in data analysis, data manipulation, and data visualization using Python. Required to have f amiliarity with healthcare-related datasets, medical terminologies, and electronic health records (EHR) data. Required to have knowledge of statistical techniques, hypothesis testing, and experimental design for healthcare research. Required to have s trong machine learning expertise: Proficient in machine learning algorithms, statistical modeling, and data analysis. Hands-on experience with standard ML frameworks (e.g., TensorFlow, PyTorch) and libraries (e.g., scikit-learn, XGBoost, TensorFlow, or Keras). Required to have solid understanding of data engineering principles, data structures, and algorithms. Proficient in Python and/or other programming languages commonly used in ML development. Required to have experience in technologies, frameworks and architecture like Java or Python, Angular, React, JSON, Application Servers, CI/CD is preferred. Required to have experience with one or more AI automations platforms like Kubeflow pipeline, MLFlow, Azure Pipeline, AWS Sage Maker Pipeline, Airflow, Jenkins, Spark, Hadoop, Kafka, Jira and GIT. We provide market-competitive compensation packages, inclusive of base pay, incentives, and benefits. The base pay rate for full-time employment is: $91,416.00 - $152,380.80. Additional compensation may be available for this role such as shift differentials, standby/on-call, overtime, premiums, extra shift incentives, or bonus opportunities. Benefits: Caring For Your Family and Your Career • Medical, Dental, Vision plans • Adoption, Fertility and Surrogacy Reimbursement up to $10,000 • Paid Time Off and Sick Leave • Paid Parental & Family Caregiver Leave • Emergency Backup Care • Long-Term, Short-Term Disability, and Critical Illness plans • Life Insurance • 401k/403B with Employer Match • Tuition Assistance - $5,250/year and discounted educational opportunities through Guild Education • Student Debt Pay Down - $10,000 • Reimbursement for certifications and free access to complete CEUs and professional development •Pet Insurance •Legal Resources Plan •Colleagues have the opportunity to earn an annual discretionary bonus ifestablished system and employee eligibility criteria is met. Sentara Health is an equal opportunity employer and prides itself on the diversity and inclusiveness of its close to an almost 30,000-member workforce. Diversity, inclusion, and belonging is a guiding principle of the organization to ensure its workforce reflects the communities it serves. In support of our mission "to improve health every day," this is a tobacco-free environment. For positions that are available as remote work, Sentara Health employs associates in the following states: Alabama, Delaware, Florida, Georgia, Idaho, Indiana, Kansas, Louisiana, Maine, Maryland, Minnesota, Nebraska, Nevada, New Hampshire, North Carolina, North Dakota, Ohio, Oklahoma, Pennsylvania, South Carolina, South Dakota, Tennessee, Texas, Utah, Virginia, Washington, West Virginia, Wisconsin, and Wyoming.
InsideHigherEd
Berkeley, California
Research Software EngineerData Scientist (6104C) - 81524 About Berkeley At the University of California, Berkeley, we are dedicated to fostering a community where everyone feels welcome and can thrive. Our culture of openness, freedom and belonging make it a special place for students, faculty and staff. As a world-leading institution, Berkeley is known for its academic and research excellence, public mission, diverse student body, and commitment to equity and social justice. Since our founding in 1868, we have driven innovation, creating global intellectual, economic and social value. We are looking for applicants who reflect California's diversity and want to be part of an inclusive, equity-focused community that views education as a matter of social justice. Please consider whether your values align with our Guiding Values and Principles , Principles of Community , and Strategic Plan . At UC Berkeley, we believe that learning is a fundamental part of working, and provide space for supportive colleague communities via numerous employee resource groups (staff organizations). Our goal is for everyone on the Berkeley campus to feel supported and equipped to realize their full potential. We actively support this by providing all of our full-time staff employees with at least 80 hours (10 days) of paid time per year to engage in professional development activities. Find out more about how you can grow your career at UC Berkeley. Departmental Overview The problems facing our environment are becoming increasingly complex and they are outpacing efforts to address them. This includes challenges ranging from climate change, to the global extinction crisis, to issues associated with environmental justice. We must act both smarter and faster to head off severe consequences for people and the planet. Data Science approaches offer a transformative opportunity to increase both the rate and impact of environmental problem-solving. Launched in 2022, the Eric and Wendy Schmidt Center for Data Science and Environment (DSE) at Berkeley ( ) is a partnership between UC Berkeley's Department of Environmental Science, Policy, and Management and the Division of Computing, Data Science, and Society, with the financial support of Eric and Wendy Schmidt, working to take on these challenges. The Center aims to contribute to the global community who are similarly working to take on these challenges in four key areas: Generating ground-breaking computational/data science discoveries motivated by pressing environmental questions; Producing scalable solutions to critical threats facing the environment, powered by open-source tools; Deploying these solutions widely, taking advantage of modern cloud infrastructure and open data/open software, and maintaining a design philosophy of vendor neutrality to ensure that community needs are prioritized; Creating an enhanced pipeline of young environmental leaders connected to local communities and organizations to meet their needs and translate our research findings and technological developments into practical impacts. The success of this effort relies on people, our ability to build upon the success of others, and to make new contributions that allow others to build on what we create. The Schmidt Center for DSE is committed to diversity, equity, inclusion, and belonging. We aim to foster an environment that is safe and open to all work together with RCNR, CDSS, and Campus to continually learn and grow in our ability to do so. Position Summary At Data Science & Environment (DSE), our engineers play a critical role in developing and delivering all technical aspects of our project efforts. We are currently looking for a candidate with strong software development experience who can also understand and support the workflows and methodologies used in biodiversity data analysis and enhancing the accessibility of bioacoustics research methods. This work is in collaboration with our partners to advance the software of Soundhub (beta: ) - a platform to store, manage, and analyze bioacoustic data. This position will play a critical role in ensuring the performance, scalability, and reliability of the data infrastructure of Soundhub and related research workflows. You have a passion for using creative coding methods to help develop and implement workflows, visualizations, and other interactive data-enabled solutions. You're driven by a commitment to protecting the environment and wildlife, and you channel that passion into bringing people together to improve tools and advance training in bioacoustic methods. As an experienced data scientist/research software engineer, you are motivated to work across diverse disciplines, advance research, and collaborate with users to ensure that human-centered design informs every stage of software development. You will lead specific projects and also engage deeply with a collaborative technical team, and opportunities to contribute your expertise across multiple projects and program areas. For examples of our project areas, learn more about our current work at . Application Review Date The First Review Date for this job is 1/21/2026 Responsibilities Plans, designs, develops, modifies, debugs, deploys and evaluates data science / computational science research software technologies and visualizations. Ensures performance, scalability, and reliability of data infrastructure and software tools developed by the core technology team. Works closely with Program Manager, Senior Research Software Engineers, and domain scientists where applicable to perform these responsibilities and uses domain science knowledge where relevant. Analyzes existing software, scientific/data science code and interactive/static visualizations or works to formulate new logic for existing systems and algorithms. Contributes to research in biodiversity monitoring workflows, with an emphasis on improving accessibility of bioacoustics research methods. Works closely with Program Manager, Senior Research Software Engineers and the program team to develop data-enabled software solutions to a given environmental challenge. Understands and applies open research and development practices, community standards and department policies and procedures relating to work assignments. May serve as technical lead for a research and development project of moderate scope. Negotiate research and development project plans with interested collaborators, stakeholders and users as applicable. Contributes research and technical content to peer-reviewed publications and program outputs. Works both independently and in collaboration with the program team and stakeholders to design and implement technical solutions to environmental challenges. Works closely with the team Program Manager to prioritize work needs and opportunities to address given needs. Documents usage modes, capabilities, characteristics and performance of research codes/software/data visualizations. Publishes and presents, based on research and development work, results about data science techniques and tools, performance and algorithm enhancement in research venues to attract usage from domain science communities, or to promote latest technologies within the community. Leads collaborations with partners, researchers, and academic institutions to advance shared goals. Communicates technical program details effectively with a wide variety of audiences to ensure understanding and engagement with program stakeholders. Required Qualifications Intermediate knowledge of open data science/research software development Advanced skills, and demonstrated experience associated with deployment of data science applications, tools, and visualizations. Demonstrated ability to regularly interface with management. Demonstrated ability to contribute research and technical content to program outputs. Demonstrated effective communication and interpersonal skills. Demonstrated ability to communicate technical information to technical and non-technical personnel at various levels in the organization and to external research and education audiences. Proven skills and experience in independently resolving broad computing/data problems using introductory and/or intermediate principles. Self-motivated and works independently and as part of a team. Able to learn effectively and meet deadlines. Proven ability to successfully work on multiple concurrent projects. Proven ability to understand research computing/data needs, mapping use cases to requirements and how systems/software/infrastructure can support those needs and meet the requirements. Demonstrated ability to develop and implement such solutions. Demonstrated experience and ability to collaborate effectively with all levels of staff; technical, students, faculty and administrators. Bachelor's degree in related area and/or equivalent experience/training. Preferred Qualifications Experience or interest in contributing to the development of applications that analyze biodiversity data, including bioacoustic data. Experience with neural networks for classifications Experience or interest in ethical considerations of data science methodologies, including open practices and data sovereignty . click apply for full job details
Research Software EngineerData Scientist (6104C) - 81524 About Berkeley At the University of California, Berkeley, we are dedicated to fostering a community where everyone feels welcome and can thrive. Our culture of openness, freedom and belonging make it a special place for students, faculty and staff. As a world-leading institution, Berkeley is known for its academic and research excellence, public mission, diverse student body, and commitment to equity and social justice. Since our founding in 1868, we have driven innovation, creating global intellectual, economic and social value. We are looking for applicants who reflect California's diversity and want to be part of an inclusive, equity-focused community that views education as a matter of social justice. Please consider whether your values align with our Guiding Values and Principles , Principles of Community , and Strategic Plan . At UC Berkeley, we believe that learning is a fundamental part of working, and provide space for supportive colleague communities via numerous employee resource groups (staff organizations). Our goal is for everyone on the Berkeley campus to feel supported and equipped to realize their full potential. We actively support this by providing all of our full-time staff employees with at least 80 hours (10 days) of paid time per year to engage in professional development activities. Find out more about how you can grow your career at UC Berkeley. Departmental Overview The problems facing our environment are becoming increasingly complex and they are outpacing efforts to address them. This includes challenges ranging from climate change, to the global extinction crisis, to issues associated with environmental justice. We must act both smarter and faster to head off severe consequences for people and the planet. Data Science approaches offer a transformative opportunity to increase both the rate and impact of environmental problem-solving. Launched in 2022, the Eric and Wendy Schmidt Center for Data Science and Environment (DSE) at Berkeley ( ) is a partnership between UC Berkeley's Department of Environmental Science, Policy, and Management and the Division of Computing, Data Science, and Society, with the financial support of Eric and Wendy Schmidt, working to take on these challenges. The Center aims to contribute to the global community who are similarly working to take on these challenges in four key areas: Generating ground-breaking computational/data science discoveries motivated by pressing environmental questions; Producing scalable solutions to critical threats facing the environment, powered by open-source tools; Deploying these solutions widely, taking advantage of modern cloud infrastructure and open data/open software, and maintaining a design philosophy of vendor neutrality to ensure that community needs are prioritized; Creating an enhanced pipeline of young environmental leaders connected to local communities and organizations to meet their needs and translate our research findings and technological developments into practical impacts. The success of this effort relies on people, our ability to build upon the success of others, and to make new contributions that allow others to build on what we create. The Schmidt Center for DSE is committed to diversity, equity, inclusion, and belonging. We aim to foster an environment that is safe and open to all work together with RCNR, CDSS, and Campus to continually learn and grow in our ability to do so. Position Summary At Data Science & Environment (DSE), our engineers play a critical role in developing and delivering all technical aspects of our project efforts. We are currently looking for a candidate with strong software development experience who can also understand and support the workflows and methodologies used in biodiversity data analysis and enhancing the accessibility of bioacoustics research methods. This work is in collaboration with our partners to advance the software of Soundhub (beta: ) - a platform to store, manage, and analyze bioacoustic data. This position will play a critical role in ensuring the performance, scalability, and reliability of the data infrastructure of Soundhub and related research workflows. You have a passion for using creative coding methods to help develop and implement workflows, visualizations, and other interactive data-enabled solutions. You're driven by a commitment to protecting the environment and wildlife, and you channel that passion into bringing people together to improve tools and advance training in bioacoustic methods. As an experienced data scientist/research software engineer, you are motivated to work across diverse disciplines, advance research, and collaborate with users to ensure that human-centered design informs every stage of software development. You will lead specific projects and also engage deeply with a collaborative technical team, and opportunities to contribute your expertise across multiple projects and program areas. For examples of our project areas, learn more about our current work at . Application Review Date The First Review Date for this job is 1/21/2026 Responsibilities Plans, designs, develops, modifies, debugs, deploys and evaluates data science / computational science research software technologies and visualizations. Ensures performance, scalability, and reliability of data infrastructure and software tools developed by the core technology team. Works closely with Program Manager, Senior Research Software Engineers, and domain scientists where applicable to perform these responsibilities and uses domain science knowledge where relevant. Analyzes existing software, scientific/data science code and interactive/static visualizations or works to formulate new logic for existing systems and algorithms. Contributes to research in biodiversity monitoring workflows, with an emphasis on improving accessibility of bioacoustics research methods. Works closely with Program Manager, Senior Research Software Engineers and the program team to develop data-enabled software solutions to a given environmental challenge. Understands and applies open research and development practices, community standards and department policies and procedures relating to work assignments. May serve as technical lead for a research and development project of moderate scope. Negotiate research and development project plans with interested collaborators, stakeholders and users as applicable. Contributes research and technical content to peer-reviewed publications and program outputs. Works both independently and in collaboration with the program team and stakeholders to design and implement technical solutions to environmental challenges. Works closely with the team Program Manager to prioritize work needs and opportunities to address given needs. Documents usage modes, capabilities, characteristics and performance of research codes/software/data visualizations. Publishes and presents, based on research and development work, results about data science techniques and tools, performance and algorithm enhancement in research venues to attract usage from domain science communities, or to promote latest technologies within the community. Leads collaborations with partners, researchers, and academic institutions to advance shared goals. Communicates technical program details effectively with a wide variety of audiences to ensure understanding and engagement with program stakeholders. Required Qualifications Intermediate knowledge of open data science/research software development Advanced skills, and demonstrated experience associated with deployment of data science applications, tools, and visualizations. Demonstrated ability to regularly interface with management. Demonstrated ability to contribute research and technical content to program outputs. Demonstrated effective communication and interpersonal skills. Demonstrated ability to communicate technical information to technical and non-technical personnel at various levels in the organization and to external research and education audiences. Proven skills and experience in independently resolving broad computing/data problems using introductory and/or intermediate principles. Self-motivated and works independently and as part of a team. Able to learn effectively and meet deadlines. Proven ability to successfully work on multiple concurrent projects. Proven ability to understand research computing/data needs, mapping use cases to requirements and how systems/software/infrastructure can support those needs and meet the requirements. Demonstrated ability to develop and implement such solutions. Demonstrated experience and ability to collaborate effectively with all levels of staff; technical, students, faculty and administrators. Bachelor's degree in related area and/or equivalent experience/training. Preferred Qualifications Experience or interest in contributing to the development of applications that analyze biodiversity data, including bioacoustic data. Experience with neural networks for classifications Experience or interest in ethical considerations of data science methodologies, including open practices and data sovereignty . click apply for full job details