STEM OPT Data Science Lead Jobs
Data Science Lead roles qualify for STEM OPT when your degree maps to an eligible CIP code in computer science, statistics, or a related STEM field. Your employer must be enrolled in E-Verify, and the 24-month extension adds up to 36 months total of post-graduation work authorization to build leadership-level experience in the U.S.
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A cover letter is required for consideration for this position and should be attached as the first page of your resume. The cover letter should address your specific interest in the position and outline skills and experience that directly relate to this position.
Mission Statement
Michigan Medicine improves the health of patients, populations and communities through excellence in education, patient care, community service, research and technology development, and through leadership activities in Michigan, nationally and internationally. Our mission is guided by our Strategic Principles and has three critical components; patient care, education and research that together enhance our contribution to society.
Job Summary
Michigan Anesthesiology Informatics and Systems Improvement Exchange (MAISE) is part of the University of Michigan Department of Anesthesiology. We are a group made up collectively of IT, business, and healthcare professionals. Our goal is to leverage IT to its fullest to improve patient safety and create better health care outcomes.
In this position, you will work under the general direction of the MAISE AIG Manager. As a Data Architect Intermediate/Senior, you will design, develop, validate, deploy, and maintain data science and artificial intelligence (AI) solutions that address clinical, operational, and research needs within Michigan Medicine. You will work with electronic health record (EHR) systems, clinical data, relational databases, and other healthcare information sources to develop machine learning models, clinical natural language processing (NLP) applications, large language model (LLM) solutions, and automated data processing pipelines.
You will leverage relational database technologies, including SQL Server, Oracle, and/or PostgreSQL, to access, transform, integrate, and manage data for AI and data science applications. You will translate clinical and operational challenges into practical, data-driven solutions through data acquisition and preprocessing, exploratory data analysis, feature engineering, model development and evaluation, AI output validation, software development, system integration, and production monitoring. You will develop custom solutions that support the EHR ecosystem and its downstream stakeholders, including Finance, Billing, Quality Assurance (QA), and Research. These solutions may involve enhancing and maintaining existing in-house applications or scoping, designing, developing, and implementing new solutions from the ground up. You will collaborate with clinicians, researchers, analysts, software developers, and IT professionals to ensure that solutions are reliable, scalable, maintainable, and appropriate for their intended use.
This position offers opportunities to contribute to innovative projects involving clinical prediction, automated clinical documentation analysis, coding and billing support, quality improvement, patient safety, and research. You will also contribute to the ongoing validation and monitoring of AI solutions to help ensure their accuracy, reliability, performance, and suitability for their intended clinical and operational applications.
Responsibilities
- Defines project requirements, scope, and objectives with clinical, operational, research, and technical stakeholders.
- Acquires, cleans, integrates, and analyzes structured and unstructured healthcare data using SQL, relational databases, EHR systems, and other data sources.
- Designs scalable data structures, data integration patterns, and reusable data pipelines to support AI applications, data science workflows, and integration across healthcare information systems.
- Develops, trains, evaluates, and optimizes machine learning and statistical models for clinical, operational, and research applications.
- Develops clinical NLP and LLM applications for information extraction, clinical summarization, structured data generation, and workflow automation.
- Builds and maintains data pipelines, ETL processes, and automated workflows for model development, validation, deployment, and production operations.
- Integrates AI solutions with existing databases, applications, and healthcare information systems.
- Validates AI outputs and model performance in collaboration with clinicians, researchers, and subject matter experts to improve accuracy and reliability.
- Develops, tests, debugs, and maintains production software and resolves issues affecting performance, scalability, and reliability.
- Monitors model performance, data quality, and system reliability; identifies issues and implements improvements.
- Proposes novel solutions to issues that arise, evaluate the feasibility of the solution, adapt and refine the model as applicable.
- Develops reports and visualizations to communicate analytical results and support clinical, operational, and research needs.
- Optimizes algorithms and workflows to improve computational efficiency, performance, and scalability.
- Documents data processing, model development, evaluation, deployment, limitations, and maintenance procedures.
- Applies appropriate data privacy, security, governance, and responsible AI practices.
- Collaborates with internal teams and external partners on data integration, research, and technical projects.
- Contributes throughout the project lifecycle, from feasibility assessment and development to implementation, maintenance, and continuous improvement.
Required Qualifications
Senior
- Bachelor's degree in Computer Science or a related field, with at least five years of directly relevant professional experience, or Master's degree in Computer Science or a related field, with at least two years of directly relevant professional experience, for the senior level.
- At least three years of programming experience in Python, R, JavaScript, C++ or another appropriate language, with demonstrated skills in SQL and data management.
- Experience in data science, machine learning, statistical analysis, software development, or related fields.
- Experience with machine learning frameworks and algorithms, including traditional machine learning, deep learning, and generative AI.
- Experience with clinical NLP, large language models (LLMs), prompt engineering, information extraction, or automated clinical documentation analysis.
- Experience developing, testing, debugging, and documenting software, data pipelines, ETL workflows, APIs, or production applications.
- Knowledge of model validation, monitoring, interpretability, reproducibility, and maintenance.
- Strong analytical, problem-solving, organizational, written communication, and presentation skills.
- Ability to work independently and collaboratively with multidisciplinary teams, and to interact effectively with diverse internal and external stakeholders.
- Ability to manage competing priorities, adapt to changing requirements, and work effectively in a fast-paced environment.
- Willingness to learn healthcare systems, clinical workflows, and new technologies.
Intermediate
- Bachelor's degree in Computer Science or a related field, with at least three years of relevant professional experience, for the intermediate level.
Candidates with extensive relevant experience and qualifications are encouraged to apply and may be considered for appointment at the senior level.
Desired Qualifications
- Master's degree in Computer Science or a related field.
- Experience with Epic, including demonstrated proficiency or relevant certification.
- Experience with electronic health record (EHR) systems, clinical databases, healthcare data standards, or Epic.
- Health system experience or experience collaborating with clinicians, researchers, or healthcare administrators.
- Familiarity with Linux, Git, automated testing, continuous integration and continuous deployment (CI/CD), containers, and production deployment.
- Experience with data warehouses, cloud or on-premises infrastructure, or GPU computing.
- Knowledge of healthcare data privacy, information security, and responsible AI practices.
Why Join Michigan Medicine?
Michigan Medicine is one of the largest health care complexes in the world and has been the site of many groundbreaking medical and technological advancements since the opening of the U-M Medical School in 1850. Michigan Medicine is comprised of over 30,000 employees and our vision is to attract, inspire, and develop outstanding people in medicine, sciences, and healthcare to become one of the world’s most distinguished academic health systems. In some way, great or small, every person here helps to advance this world-class institution. Work at Michigan Medicine and become a victor for the greater good.
What Benefits can you Look Forward to?
- Excellent medical, dental and vision coverage effective on your very first day
- 2:1 Match on retirement savings
Modes of Work
Positions that are eligible for hybrid or mobile/remote work mode are at the discretion of the hiring department. Work agreements are reviewed annually at a minimum and are subject to change at any time, and for any reason, throughout the course of employment. Learn more about the work modes.
Underfill Statement
This position may be underfilled at a lower classification depending on the qualifications of the selected candidate.
Background Screening
Michigan Medicine conducts background screening and pre-employment drug testing on job candidates upon acceptance of a contingent job offer and may use a third party administrator to conduct background screenings. Background screenings are performed in compliance with the Fair Credit Report Act. Pre-employment drug testing applies to all selected candidates, including new or additional faculty and staff appointments, as well as transfers from other U-M campuses.
Application Deadline
Job openings are posted for a minimum of seven calendar days. The review and selection process may begin as early as the eighth day after posting. This opening may be removed from posting boards and filled anytime after the minimum posting period has ended.
U-M EEO Statement
The University of Michigan is an Equal Opportunity Employer. We are committed to providing an environment of mutual respect where equal employment opportunities are available to all applicants, including protected veterans and individuals with disabilities.
Job Opening ID
285219
Working Title
Data Science Analyst Senior/Intermediate
Job Title
Data Architect Senior
Work Location
Ann Arbor Campus
Ann Arbor, MI
Modes of Work
Onsite
Full/Part Time
Full-Time
Regular/Temporary
Regular
FLSA Status
Exempt
Organizational Group
Medical School
Department
MM Anesthesiology Department
Posting Begin/End Date
11/03/2026 - 12/03/2026
Career Interest
Information Technology
How to Apply
A cover letter is required for consideration for this position and should be attached as the first page of your resume. The cover letter should address your specific interest in the position and outline skills and experience that directly relate to this position.
Mission Statement
Michigan Medicine improves the health of patients, populations and communities through excellence in education, patient care, community service, research and technology development, and through leadership activities in Michigan, nationally and internationally. Our mission is guided by our Strategic Principles and has three critical components; patient care, education and research that together enhance our contribution to society.
Job Summary
Michigan Anesthesiology Informatics and Systems Improvement Exchange (MAISE) is part of the University of Michigan Department of Anesthesiology. We are a group made up collectively of IT, business, and healthcare professionals. Our goal is to leverage IT to its fullest to improve patient safety and create better health care outcomes.
In this position, you will work under the general direction of the MAISE AIG Manager. As a Data Architect Intermediate/Senior, you will design, develop, validate, deploy, and maintain data science and artificial intelligence (AI) solutions that address clinical, operational, and research needs within Michigan Medicine. You will work with electronic health record (EHR) systems, clinical data, relational databases, and other healthcare information sources to develop machine learning models, clinical natural language processing (NLP) applications, large language model (LLM) solutions, and automated data processing pipelines.
You will leverage relational database technologies, including SQL Server, Oracle, and/or PostgreSQL, to access, transform, integrate, and manage data for AI and data science applications. You will translate clinical and operational challenges into practical, data-driven solutions through data acquisition and preprocessing, exploratory data analysis, feature engineering, model development and evaluation, AI output validation, software development, system integration, and production monitoring. You will develop custom solutions that support the EHR ecosystem and its downstream stakeholders, including Finance, Billing, Quality Assurance (QA), and Research. These solutions may involve enhancing and maintaining existing in-house applications or scoping, designing, developing, and implementing new solutions from the ground up. You will collaborate with clinicians, researchers, analysts, software developers, and IT professionals to ensure that solutions are reliable, scalable, maintainable, and appropriate for their intended use.
This position offers opportunities to contribute to innovative projects involving clinical prediction, automated clinical documentation analysis, coding and billing support, quality improvement, patient safety, and research. You will also contribute to the ongoing validation and monitoring of AI solutions to help ensure their accuracy, reliability, performance, and suitability for their intended clinical and operational applications.
Responsibilities
- Defines project requirements, scope, and objectives with clinical, operational, research, and technical stakeholders.
- Acquires, cleans, integrates, and analyzes structured and unstructured healthcare data using SQL, relational databases, EHR systems, and other data sources.
- Designs scalable data structures, data integration patterns, and reusable data pipelines to support AI applications, data science workflows, and integration across healthcare information systems.
- Develops, trains, evaluates, and optimizes machine learning and statistical models for clinical, operational, and research applications.
- Develops clinical NLP and LLM applications for information extraction, clinical summarization, structured data generation, and workflow automation.
- Builds and maintains data pipelines, ETL processes, and automated workflows for model development, validation, deployment, and production operations.
- Integrates AI solutions with existing databases, applications, and healthcare information systems.
- Validates AI outputs and model performance in collaboration with clinicians, researchers, and subject matter experts to improve accuracy and reliability.
- Develops, tests, debugs, and maintains production software and resolves issues affecting performance, scalability, and reliability.
- Monitors model performance, data quality, and system reliability; identifies issues and implements improvements.
- Proposes novel solutions to issues that arise, evaluate the feasibility of the solution, adapt and refine the model as applicable.
- Develops reports and visualizations to communicate analytical results and support clinical, operational, and research needs.
- Optimizes algorithms and workflows to improve computational efficiency, performance, and scalability.
- Documents data processing, model development, evaluation, deployment, limitations, and maintenance procedures.
- Applies appropriate data privacy, security, governance, and responsible AI practices.
- Collaborates with internal teams and external partners on data integration, research, and technical projects.
- Contributes throughout the project lifecycle, from feasibility assessment and development to implementation, maintenance, and continuous improvement.
Required Qualifications
Senior
- Bachelor's degree in Computer Science or a related field, with at least five years of directly relevant professional experience, or Master's degree in Computer Science or a related field, with at least two years of directly relevant professional experience, for the senior level.
- At least three years of programming experience in Python, R, JavaScript, C++ or another appropriate language, with demonstrated skills in SQL and data management.
- Experience in data science, machine learning, statistical analysis, software development, or related fields.
- Experience with machine learning frameworks and algorithms, including traditional machine learning, deep learning, and generative AI.
- Experience with clinical NLP, large language models (LLMs), prompt engineering, information extraction, or automated clinical documentation analysis.
- Experience developing, testing, debugging, and documenting software, data pipelines, ETL workflows, APIs, or production applications.
- Knowledge of model validation, monitoring, interpretability, reproducibility, and maintenance.
- Strong analytical, problem-solving, organizational, written communication, and presentation skills.
- Ability to work independently and collaboratively with multidisciplinary teams, and to interact effectively with diverse internal and external stakeholders.
- Ability to manage competing priorities, adapt to changing requirements, and work effectively in a fast-paced environment.
- Willingness to learn healthcare systems, clinical workflows, and new technologies.
Intermediate
- Bachelor's degree in Computer Science or a related field, with at least three years of relevant professional experience, for the intermediate level.
Candidates with extensive relevant experience and qualifications are encouraged to apply and may be considered for appointment at the senior level.
Desired Qualifications
- Master's degree in Computer Science or a related field.
- Experience with Epic, including demonstrated proficiency or relevant certification.
- Experience with electronic health record (EHR) systems, clinical databases, healthcare data standards, or Epic.
- Health system experience or experience collaborating with clinicians, researchers, or healthcare administrators.
- Familiarity with Linux, Git, automated testing, continuous integration and continuous deployment (CI/CD), containers, and production deployment.
- Experience with data warehouses, cloud or on-premises infrastructure, or GPU computing.
- Knowledge of healthcare data privacy, information security, and responsible AI practices.
Why Join Michigan Medicine?
Michigan Medicine is one of the largest health care complexes in the world and has been the site of many groundbreaking medical and technological advancements since the opening of the U-M Medical School in 1850. Michigan Medicine is comprised of over 30,000 employees and our vision is to attract, inspire, and develop outstanding people in medicine, sciences, and healthcare to become one of the world’s most distinguished academic health systems. In some way, great or small, every person here helps to advance this world-class institution. Work at Michigan Medicine and become a victor for the greater good.
What Benefits can you Look Forward to?
- Excellent medical, dental and vision coverage effective on your very first day
- 2:1 Match on retirement savings
Modes of Work
Positions that are eligible for hybrid or mobile/remote work mode are at the discretion of the hiring department. Work agreements are reviewed annually at a minimum and are subject to change at any time, and for any reason, throughout the course of employment. Learn more about the work modes.
Underfill Statement
This position may be underfilled at a lower classification depending on the qualifications of the selected candidate.
Background Screening
Michigan Medicine conducts background screening and pre-employment drug testing on job candidates upon acceptance of a contingent job offer and may use a third party administrator to conduct background screenings. Background screenings are performed in compliance with the Fair Credit Report Act. Pre-employment drug testing applies to all selected candidates, including new or additional faculty and staff appointments, as well as transfers from other U-M campuses.
Application Deadline
Job openings are posted for a minimum of seven calendar days. The review and selection process may begin as early as the eighth day after posting. This opening may be removed from posting boards and filled anytime after the minimum posting period has ended.
U-M EEO Statement
The University of Michigan is an Equal Opportunity Employer. We are committed to providing an environment of mutual respect where equal employment opportunities are available to all applicants, including protected veterans and individuals with disabilities.
Job Opening ID
285219
Working Title
Data Science Analyst Senior/Intermediate
Job Title
Data Architect Senior
Work Location
Ann Arbor Campus
Ann Arbor, MI
Modes of Work
Onsite
Full/Part Time
Full-Time
Regular/Temporary
Regular
FLSA Status
Exempt
Organizational Group
Medical School
Department
MM Anesthesiology Department
Posting Begin/End Date
11/03/2026 - 12/03/2026
Career Interest
Information Technology
See all STEM OPT Data Science Lead Jobs
Sign up for free to unlock all listings, filter by visa type, and get alerts for new STEM OPT Data Science Lead Jobs.
Get Access To All JobsTips for Finding STEM OPT Authorization in Data Science Lead
Verify your CIP code before applying
Check that your degree's CIP code appears on the STEM Designated Degree Program List maintained by USCIS. Data science degrees sometimes map to statistics or computer science codes rather than a standalone data science category, so confirm with your DSO before targeting roles.
Confirm E-Verify enrollment before accepting offers
Ask hiring managers directly whether the company is enrolled in E-Verify before you reach the offer stage. STEM OPT authorization is void if your employer isn't enrolled, and many mid-size analytics firms haven't completed enrollment even when they're otherwise willing to hire OPT students.
Target companies with active data science LCA filings
Use the OFLC Wage Search to find employers who have filed Labor Condition Applications for data science or machine learning roles. Companies with recent LCA activity are already familiar with the compliance steps that overlap with STEM OPT employer obligations.
Build an I-983 training plan around leadership deliverables
For a Data Science Lead role, your I-983 should document mentorship responsibilities, model deployment ownership, and cross-functional project outcomes, not just technical tasks. A vague training plan tied only to tools or coding work is harder to defend at the 12-month evaluation.
Use Migrate Mate to find STEM OPT eligible Data Science Lead openings
Filter your search on Migrate Mate to surface Data Science Lead roles at E-Verify enrolled employers. This removes the manual step of cross-checking employer eligibility and lets you focus on companies already set up to support STEM OPT training plans and reporting requirements.
Address cap-gap timing during salary and start-date negotiations
If your OPT expires while an H-1B visa petition is pending, cap-gap rules extend your authorization through September 30. Negotiating a start date that accounts for this window prevents a gap that would otherwise force you to pause in a leadership role mid-project.
Frequently Asked Questions
Does a Data Science Lead role qualify for STEM OPT?
Yes, if your degree carries an eligible CIP code in computer science, statistics, information science, or a related STEM field, and the Data Science Lead position requires applying that technical training directly. Your DSO must recommend the STEM OPT extension on your I-20, and your employer must be enrolled in E-Verify. The O*NET occupation profile for data science roles supports the STEM designation when the job duties align with your degree field.
What E-Verify requirements apply to my employer for STEM OPT?
Your employer must be enrolled in E-Verify as a condition of hiring you on STEM OPT. Enrollment must be active before your extension begins, not just initiated. The employer also needs to sign the I-983 training plan and submit a formal evaluation at the 12-month mark. If your employer is not enrolled, your STEM OPT authorization doesn't apply, regardless of how well the role matches your degree.
What should the I-983 training plan include for a Data Science Lead?
The I-983 must connect your daily work to the learning objectives tied to your STEM degree. For a Data Science Lead, that means documenting responsibilities like designing modeling pipelines, leading analytical projects, or mentoring junior team members as practical applications of your academic training. Generic descriptions of tools used aren't sufficient. USCIS expects the plan to show how the role advances skills within your specific degree field.
How does cap-gap protection affect a Data Science Lead on STEM OPT?
If you're on STEM OPT and your employer files an H-1B petition before your authorization expires, cap-gap rules allow you to keep working through September 30 of that fiscal year while the petition is pending. For a Data Science Lead managing ongoing projects, this means you can stay in your role without interruption during the transition window. USCIS issues an updated I-20 reflecting the cap-gap extension to document the continued authorization.
Where can I find Data Science Lead jobs that support STEM OPT?
Migrate Mate lists Data Science Lead openings at employers already enrolled in E-Verify, so you can focus your search on companies set up to support STEM OPT training plans and reporting requirements. Filtering by STEM OPT eligibility at the start of your search saves significant time compared to vetting employer enrollment status manually after finding a role through a general job board.