STEM OPT Data Science Analyst Jobs
Data Science Analyst roles sit squarely within STEM OPT eligibility, giving you up to 24 additional months of work authorization beyond your initial OPT period. Your employer must be enrolled in E-Verify, and your degree in statistics, computer science, mathematics, or a related STEM field must align with the role's CIP code to qualify.
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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 Analyst Jobs
Sign up for free to unlock all listings, filter by visa type, and get alerts for new STEM OPT Data Science Analyst Jobs.
Get Access To All JobsTips for Finding STEM OPT Authorization as a Data Science Analyst
Verify your CIP code before applying
Cross-reference your degree's Classification of Instructional Programs code against the STEM-designated degree list published by USCIS. Data Science Analyst roles typically align with CIP codes in statistics, computer science, or mathematics. A mismatch disqualifies your STEM OPT extension before it starts.
Confirm E-Verify enrollment before accepting offers
Ask recruiters directly whether the company is enrolled in E-Verify before you invest time in later-stage interviews. You can verify enrollment through the E-Verify employer search. Smaller analytics teams and startups frequently overlook this requirement, so don't assume compliance based on company size.
Use O*NET to anchor your I-983 training plan
O*NET lists the core tasks and knowledge areas for Data Science Analyst roles. Pull those directly into your I-983 training plan goals so your DSO and employer can document how your daily work develops STEM skills. Vague training plans draw scrutiny during DSO review.
Target employers with active data science LCA filings
Search Migrate Mate to find employers with verified Labor Condition Application filings for data science roles. Companies already filing LCAs for similar positions have the HR and legal infrastructure to support your STEM OPT paperwork without building the process from scratch.
File your STEM OPT extension 90 days before OPT expires
USCIS requires you to submit your STEM OPT extension application no earlier than 90 days before your current EAD expires. Your DSO must recommend the extension in SEVIS before you file Form I-765. Missing this window forces a gap in your work authorization.
Negotiate your start date around cap-gap protection
If you're transitioning from STEM OPT to an H-1B visa, cap-gap automatically extends your work authorization through September 30 of the fiscal year your H-1B petition was filed. Confirm your employer understands this rule so your offer letter and start date don't conflict with your authorization period.
Frequently Asked Questions
Does a Data Science Analyst role qualify for the STEM OPT extension?
Yes, if your employer is enrolled in E-Verify and your underlying degree is in a STEM-designated field such as statistics, computer science, mathematics, or data science. Your degree's CIP code must appear on the USCIS STEM-designated degree list. The Data Science Analyst role itself must also demonstrably use your STEM training, which you document in the I-983 training plan filed with your DSO.
What STEM degrees make you eligible for the STEM OPT extension in a data analyst role?
Degrees in statistics, computer science, mathematics, information systems, applied mathematics, and data science are commonly eligible. Your eligibility depends on the specific CIP code assigned to your program, not just the degree title. Confirm your CIP code against the USCIS STEM-designated degree list before your DSO submits the STEM OPT recommendation in SEVIS. A degree labeled 'Business Analytics' may or may not qualify depending on the CIP code.
How do I find Data Science Analyst employers who are enrolled in E-Verify?
You can search Migrate Mate to browse Data Science Analyst positions at employers with verified sponsorship history. Before accepting any offer, ask the recruiter directly whether the company is currently enrolled in E-Verify, and confirm through the E-Verify employer search tool. E-Verify enrollment is a legal prerequisite for hiring STEM OPT students, but not every employer advertising data roles has completed enrollment.
What goes into the I-983 training plan for a Data Science Analyst position?
Your I-983 must describe the specific STEM knowledge, skills, and competencies you'll develop in the role, the supervision structure, and how the work connects to your degree field. For a Data Science Analyst position, this typically includes machine learning model development, statistical analysis, data pipeline work, or predictive modeling tasks. Use O*NET's task and knowledge descriptions for the occupation to build out the training goals section with language your DSO can approve without revision.
What happens to my STEM OPT authorization if my employer loses E-Verify enrollment?
If your employer's E-Verify participation is terminated, your STEM OPT authorization is no longer valid with that employer. You have a 60-day grace period to find a new E-Verify-enrolled employer, change your immigration status, or depart the country. Notify your DSO immediately, because the clock on that grace period starts from the date the employer's enrollment ends, not from when you find out.