OPT Data And Analytics Jobs
Data and analytics roles are among the most OPT-friendly in the U.S. job market. Employers across finance, tech, healthcare, and retail routinely sponsor F-1 students, and STEM OPT extension eligibility means you can work up to three years without H-1B visa status.
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A healthier future. It’s what drives us to innovate. To continuously advance science and ensure everyone has access to the healthcare they need today and for generations to come. Creating a world where we all have more time with the people we love. That’s what makes us Roche.
This role is based in the Real-World & Clinical Data Strategy (RWCDS) team which drives data excellence and analytics to power enhanced decision-making and evidence-generation within Roche Product Development. We develop and implement data strategies that unlock the value of clinical, operational, and real-world data to accelerate evidence generation, decision-making, and innovation across PD and beyond. By embedding FAIR principles, advancing data governance, and enabling data productization, RWCDS ensures that data is not only findable and usable, but also a driver of scientific rigor, regulatory readiness, and AI-powered transformation. Through deep partnerships with internal functions and external collaborators, we shape a future-ready data ecosystem that supports personalized healthcare and efficient drug development.
The Opportunity:
The Data Strategy & Analytics Specialist contributes to the design and execution of data strategies and analyses that enable decision-making and insight generation across a therapeutic area or molecule portfolio. Working under the Data Strategy & Analytics Lead, you will partner with cross-functional teams—translating scientific protocols into robust analytical code, cohort extractions, and reproducible pipelines using multi-modal real-world data and clinical assets. You will also contribute to the translation of scientific and business needs into analytical frameworks and data-driven solutions. This role demands strong core data science skills, analytical execution, and a growth mindset to continuously elevate team standards.
- You execute data transformations, cohort extractions, and descriptive/observational analyses leveraging real-world (EHR, Claims, etc.), clinical trial data for secondary use, and operational multi-modal domains.
- You translate analytical or study requirements into cohort definitions, derived variables, and analysis-ready datasets.
- You follow state-of-the-art coding best practices, version control, unit testing, and structured QC routines to guarantee fully reproducible analytical pipelines.
- You summarize and visualize exploratory analytical outputs, cohort characteristics, and study results to communicate findings effectively to project teams.
- You partner seamlessly with RWD Scientists and cross-functional study leads during study framing and protocol development, providing active feedback on data availability, feasibility, methodology, and execution.
- You actively contribute well-documented code snippets, analytical templates, and learnings to the internal team repository.
- You assist in identifying fit-for-purpose real-world data (RWD) sources, performing data quality evaluations, terminology mappings, and schema transformations for secondary data use.
- You partner with study teams and central data engineering functions to gather analysis requirements, specify derived variables (e.g., ADaM, ARDs), and shape clinical trial datamarts for secondary use.
- You collaborate with central data engineering and governance teams to guide multi-modal data integration, applying common data models (OMOP, CDISC) and structured mappings across clinical trial and real-world assets.
- You collaborate with internal partners to analyze data structures, document data lineage, and maintain structured, compliant, and accessible data assets to support long-term data strategy and reusability.
- You safely leverage modern AI coding tools and LLM assistants (e.g., Claude Code, Copilot) to accelerate scripting, query building, and data extraction while maintaining scientific rigor and code quality.
Who you are:
- You hold a Bachelor’s or Master’s degree in Informatics, Life Sciences, Computer Science, or a related field.
- You have 2+ years of experience working with structured data in a research or healthcare setting.
- You have solid working knowledge of R or Python, as well as SQL.
- You understand data dictionaries, mappings, or metadata tagging.
- You are familiar with data systems used in clinical or operational settings.
- You demonstrate capacity for independent thinking and ability to make decisions based upon sound principles.
- You exhibit excellent strategic agility including problem-solving and critical thinking skills, and agility that extends beyond the technical domain.
- You demonstrate respect for cultural differences when interacting with colleagues in the global workplace.
- You possess excellent verbal and written communication skills, specifically in the areas of presentation and writing, with the ability to explain complex technical concepts in clear language.
Preferred Qualifications:
- Working knowledge of descriptive statistical methods and epidemiological concepts used in observational healthcare research (e.g., cohort identification, censoring, time-to-event concepts).
- Prior experience in cardiovascular, renal, or metabolic (CVRM) therapeutic areas.
- Familiarity with clinical terminologies and coding systems, including ICD, SNOMED CT, RxNorm, CPT, and HCPCS.
- Exposure to real-world data common data models (e.g., OMOP CDM) or CDISC standards (SDTM, ADaM).
- Familiarity with software engineering best practices (Git, unit testing) and AI-assisted coding tools (e.g., Claude Code, GitHub Copilot).
Location:
This position is based in Boston, Massachusetts. Relocation benefits are not available for this posting.
The expected salary range for this position based on the primary location of Massachusetts is $89,400.00 - $166,000.00 USD Annual. Actual pay will be determined based on experience, qualifications, geographic location, and other job-related factors permitted by law. A discretionary annual bonus may be available based on individual and Company performance. This position also qualifies for the benefits detailed at the link provided below.
Benefits
Genentech is an equal opportunity employer. It is our policy and practice to employ, promote, and otherwise treat any and all employees and applicants on the basis of merit, qualifications, and competence. The company's policy prohibits unlawful discrimination, including but not limited to, discrimination on the basis of Protected Veteran status, individuals with disabilities status, and consistent with all federal, state, or local laws.
If you have a disability and need an accommodation in relation to the online application process, please contact us by completing this form Accommodations for Applicants.
The Position
A healthier future. It’s what drives us to innovate. To continuously advance science and ensure everyone has access to the healthcare they need today and for generations to come. Creating a world where we all have more time with the people we love. That’s what makes us Roche.
This role is based in the Real-World & Clinical Data Strategy (RWCDS) team which drives data excellence and analytics to power enhanced decision-making and evidence-generation within Roche Product Development. We develop and implement data strategies that unlock the value of clinical, operational, and real-world data to accelerate evidence generation, decision-making, and innovation across PD and beyond. By embedding FAIR principles, advancing data governance, and enabling data productization, RWCDS ensures that data is not only findable and usable, but also a driver of scientific rigor, regulatory readiness, and AI-powered transformation. Through deep partnerships with internal functions and external collaborators, we shape a future-ready data ecosystem that supports personalized healthcare and efficient drug development.
The Opportunity:
The Data Strategy & Analytics Specialist contributes to the design and execution of data strategies and analyses that enable decision-making and insight generation across a therapeutic area or molecule portfolio. Working under the Data Strategy & Analytics Lead, you will partner with cross-functional teams—translating scientific protocols into robust analytical code, cohort extractions, and reproducible pipelines using multi-modal real-world data and clinical assets. You will also contribute to the translation of scientific and business needs into analytical frameworks and data-driven solutions. This role demands strong core data science skills, analytical execution, and a growth mindset to continuously elevate team standards.
- You execute data transformations, cohort extractions, and descriptive/observational analyses leveraging real-world (EHR, Claims, etc.), clinical trial data for secondary use, and operational multi-modal domains.
- You translate analytical or study requirements into cohort definitions, derived variables, and analysis-ready datasets.
- You follow state-of-the-art coding best practices, version control, unit testing, and structured QC routines to guarantee fully reproducible analytical pipelines.
- You summarize and visualize exploratory analytical outputs, cohort characteristics, and study results to communicate findings effectively to project teams.
- You partner seamlessly with RWD Scientists and cross-functional study leads during study framing and protocol development, providing active feedback on data availability, feasibility, methodology, and execution.
- You actively contribute well-documented code snippets, analytical templates, and learnings to the internal team repository.
- You assist in identifying fit-for-purpose real-world data (RWD) sources, performing data quality evaluations, terminology mappings, and schema transformations for secondary data use.
- You partner with study teams and central data engineering functions to gather analysis requirements, specify derived variables (e.g., ADaM, ARDs), and shape clinical trial datamarts for secondary use.
- You collaborate with central data engineering and governance teams to guide multi-modal data integration, applying common data models (OMOP, CDISC) and structured mappings across clinical trial and real-world assets.
- You collaborate with internal partners to analyze data structures, document data lineage, and maintain structured, compliant, and accessible data assets to support long-term data strategy and reusability.
- You safely leverage modern AI coding tools and LLM assistants (e.g., Claude Code, Copilot) to accelerate scripting, query building, and data extraction while maintaining scientific rigor and code quality.
Who you are:
- You hold a Bachelor’s or Master’s degree in Informatics, Life Sciences, Computer Science, or a related field.
- You have 2+ years of experience working with structured data in a research or healthcare setting.
- You have solid working knowledge of R or Python, as well as SQL.
- You understand data dictionaries, mappings, or metadata tagging.
- You are familiar with data systems used in clinical or operational settings.
- You demonstrate capacity for independent thinking and ability to make decisions based upon sound principles.
- You exhibit excellent strategic agility including problem-solving and critical thinking skills, and agility that extends beyond the technical domain.
- You demonstrate respect for cultural differences when interacting with colleagues in the global workplace.
- You possess excellent verbal and written communication skills, specifically in the areas of presentation and writing, with the ability to explain complex technical concepts in clear language.
Preferred Qualifications:
- Working knowledge of descriptive statistical methods and epidemiological concepts used in observational healthcare research (e.g., cohort identification, censoring, time-to-event concepts).
- Prior experience in cardiovascular, renal, or metabolic (CVRM) therapeutic areas.
- Familiarity with clinical terminologies and coding systems, including ICD, SNOMED CT, RxNorm, CPT, and HCPCS.
- Exposure to real-world data common data models (e.g., OMOP CDM) or CDISC standards (SDTM, ADaM).
- Familiarity with software engineering best practices (Git, unit testing) and AI-assisted coding tools (e.g., Claude Code, GitHub Copilot).
Location:
This position is based in Boston, Massachusetts. Relocation benefits are not available for this posting.
The expected salary range for this position based on the primary location of Massachusetts is $89,400.00 - $166,000.00 USD Annual. Actual pay will be determined based on experience, qualifications, geographic location, and other job-related factors permitted by law. A discretionary annual bonus may be available based on individual and Company performance. This position also qualifies for the benefits detailed at the link provided below.
Benefits
Genentech is an equal opportunity employer. It is our policy and practice to employ, promote, and otherwise treat any and all employees and applicants on the basis of merit, qualifications, and competence. The company's policy prohibits unlawful discrimination, including but not limited to, discrimination on the basis of Protected Veteran status, individuals with disabilities status, and consistent with all federal, state, or local laws.
If you have a disability and need an accommodation in relation to the online application process, please contact us by completing this form Accommodations for Applicants.
See all 727+ OPT Data And Analytics Jobs
Sign up for free to unlock all listings, filter by visa type, and get alerts for new OPT Data And Analytics Jobs.
Get Access To All JobsTips for Finding OPT Sponsorship in Data And Analytics
Lead with your STEM OPT eligibility
Data science, analytics, and statistics degrees almost universally qualify for the 24-month STEM OPT extension. Tell employers upfront. It reframes you from a short-term hire into a three-year runway, which meaningfully reduces sponsorship hesitation.
Target companies with existing OPT hiring patterns
Employers who have hired OPT students before understand the paperwork and timeline. Look for job postings that explicitly mention OPT or CPT authorization. These companies have cleared the internal approval hurdles that first-time sponsors haven't.
Quantify your impact with data, not just tools
Listing Python, SQL, and Tableau is table stakes. Employers remember candidates who say they reduced churn by 12% or cut reporting time in half. Specific, quantified outcomes signal readiness to contribute from day one.
Apply before your OPT start date whenever possible
Most OPT work authorization takes 3 to 5 months to process after your I-20 is issued. Starting your job search during your final semester gives employers time to hire without feeling rushed by your authorization timeline.
Be specific about your authorization window in outreach
When a recruiter asks about work authorization, give exact dates. Saying your OPT runs through May 2027 and is STEM-extendable through May 2029 is far more actionable than saying you need sponsorship eventually.
Build a portfolio that removes uncertainty about your skills
A GitHub repo with a real-world dataset analysis or a dashboard built on public data does what a resume cannot. It lets employers evaluate your actual work before the interview, which reduces perceived hiring risk significantly.
Data And Analytics OPT: Frequently Asked Questions
Do data and analytics roles qualify for the STEM OPT extension?
Most do. Degrees in data science, statistics, computer science, information systems, and applied mathematics are on the STEM Designated Degree Program List. If your degree qualifies and your employer enrolls in E-Verify, you can extend OPT by 24 months beyond your initial 12-month period, giving you up to three years of work authorization total.
How do I find data and analytics employers who sponsor OPT students?
Migrate Mate lists data and analytics roles specifically filtered for OPT-eligible candidates. Large technology companies, financial institutions, healthcare systems, and consulting firms are the most consistent sponsors. Smaller startups can sponsor but often lack an established immigration process, so verifying their E-Verify enrollment before applying saves time.
Can I work as a data analyst or data scientist on day-one OPT before the STEM extension?
Yes. Your initial 12 months of OPT authorize full-time employment in any role directly related to your degree field. You do not need to wait for STEM extension approval. Once you are within 90 days of your initial OPT expiration, you can apply for the STEM extension while continuing to work.
What employer requirements apply specifically during the STEM OPT extension period?
During the 24-month STEM extension, your employer must be enrolled in E-Verify, provide a formal training plan using USCIS Form I-983, and report material changes to your role or compensation to your Designated School Official. The job must be directly related to your STEM degree. Self-employment and contract arrangements through staffing agencies are not permitted during this period.
Does working in data analytics improve my H-1B sponsorship odds after OPT?
Data and analytics roles are among the most commonly sponsored specialty occupations under H-1B visa. Employers in finance, technology, and healthcare have strong track records of filing H-1B petitions for analysts and data scientists. The STEM OPT extension gives you up to three years to build a relationship with an employer before the H-1B cap lottery becomes your primary concern.