STEM OPT Data Science Engineer Jobs
Data Science Engineer roles sit squarely within STEM OPT eligibility, letting you work for up to 36 months on your F-1 authorization if your employer is enrolled in E-Verify. Your STEM degree in computer science, statistics, or a related field qualifies you for the 24-month extension, giving you real runway to build U.S. experience.
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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 Engineer Jobs
Sign up for free to unlock all listings, filter by visa type, and get alerts for new STEM OPT Data Science Engineer Jobs.
Get Access To All JobsTips for Finding STEM OPT Authorization as a Data Science Engineer
Verify your CIP code before applying
Check that your degree's Classification of Instructional Programs code maps to a DHS-designated STEM field. Data science and computer science degrees typically qualify, but applied mathematics or information systems programs vary by institution and award year.
Confirm E-Verify enrollment before accepting offers
Your employer must be enrolled in E-Verify before your STEM OPT extension start date, not after. Search the E-Verify employer database by company name or EIN to confirm active enrollment before you sign anything.
Research prevailing wages using OFLC Wage Search
Data Science Engineer salaries vary sharply by location and experience level. Pull the prevailing wage for your specific SOC code and metro area using OFLC Wage Search so you can negotiate from a position grounded in DOL wage data.
Target employers with active LCA filing history
Use Migrate Mate to filter Data Science Engineer roles by employers who have filed Labor Condition Applications, which signals both E-Verify enrollment and familiarity with the STEM OPT and H-1B visa process your career path will likely require.
Negotiate your I-983 training plan before your start date
The I-983 must detail specific learning objectives tied to your STEM degree, not just your job description. Bring a draft to the offer stage so your DSO can review it alongside your start date rather than scrambling after you've already begun work.
Time your extension application around the 90-day window
USCIS requires you to file your STEM OPT extension before your initial OPT EAD expires. Apply within the 90-day window that opens before expiration so a timely filing keeps you authorized while USCIS adjudicates.
Frequently Asked Questions
Does a data science or computer science degree qualify for the STEM OPT extension?
Most data science, computer science, statistics, and engineering degrees qualify because they map to DHS-designated CIP codes. Applied mathematics and information systems programs sometimes qualify depending on how your institution coded the award. Confirm your exact CIP code with your DSO before your initial OPT ends, since the designation is tied to the degree on your I-20, not your job title.
What E-Verify requirement applies to Data Science Engineer STEM OPT jobs?
Your employer must be actively enrolled in E-Verify before your STEM OPT extension period begins. Enrollment after your start date does not satisfy the requirement. You can verify a company's enrollment status by searching the E-Verify employer database by company name or EIN. If the employer isn't listed, your DSO cannot approve the I-983 training plan and your extension will be at risk.
What goes into the I-983 training plan for a Data Science Engineer role?
The I-983 must connect your specific work activities to the STEM field of your degree. For a Data Science Engineer role, that means detailing the models you'll build, the data pipelines you'll own, and the engineering methods you'll apply, alongside measurable learning objectives. Generic job descriptions aren't sufficient. Your employer's HR or engineering lead signs the plan, and your DSO must approve it before USCIS adjudicates the extension.
How does cap-gap protection work if I'm a Data Science Engineer on STEM OPT?
If your employer files an H-1B petition on your behalf before your STEM OPT EAD expires and you're selected in the lottery, cap-gap automatically extends your work authorization through September 30 of that fiscal year. You can continue working as a Data Science Engineer during this bridge period without a new EAD. USCIS provides guidance on cap-gap eligibility and documentation requirements.
Where can I find Data Science Engineer jobs where the employer is already set up for STEM OPT?
Migrate Mate filters Data Science Engineer listings by employers with active Labor Condition Application filing history, which indicates both E-Verify enrollment and prior experience sponsoring international candidates. Searching there saves you from spending weeks in a recruiting process only to discover the employer has never hired on OPT and isn't enrolled in E-Verify.