Research Data Scientist Jobs
Research Data Scientist jobs are open across technology, healthcare, finance, and academia, from entry-level to principal and staff, with specializations in machine learning research, statistical modeling, and natural language processing. Find a role that fits from the openings below and apply directly.
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Showing 5 of 64+ Research Data Scientist jobs
Patient care: We promote health and provide superb clinical care while maintaining our strong tradition of reaching underserved populations and reducing health disparities across North Carolina and beyond.
Education: We prepare tomorrow’s healthcare professionals and biomedical researchers from all backgrounds by facilitating learning within innovative and integrated curricula and team-oriented interprofessional education to ensure a highly skilled workforce.
Research: We develop and support a rich array of outstanding health sciences research programs, centers and resources. We provide infrastructure and opportunities for collaboration among disciplines throughout and beyond our university to support outstanding research. We foster programs in the areas of basic, translational, mechanistic and population research.
- Professional and/or formal educational experience utilizing large language models for research, including deploying, tuning, and optimizing open- and closed-source models in local and cloud environments, including high-security or air-gapped environments for sensitive data
- Experience applying LLMs to structured information extraction from unstructured text (e.g., named entity recognition, relation extraction, schema-constrained or function-calling-based structured output generation)
- Experience with natural language processing utilizing traditional data science approaches (word2Vec, NLTK, Spark NLP, etc.) and/or NLP utilizing large language models
- High level of proficiency in either R or Python in the areas of machine learning, deep learning, statistical analysis, computer vision, and/or graph analysis
- Experience with data engineering to create data science pipelines, deploy and scale models, and maintain and thoroughly document code and models, including designing evaluation frameworks for model/pipeline accuracy (e.g., precision/recall/F1 against gold-standard human annotation
- Knowledge of SQL programming, data modeling, and relational database systems such as Oracle, MS-SQL, MySQL, etc.
- Highly capable of working in a cross-functional team and functioning as lead scientist on research and development efforts – ability to manage multiple projects at once while delivering high-quality work on time
- Strong interest in clinical data and desire to develop deep expertise in EHR and claims data; interest in developing deep expertise in cancer registry data standards and abstraction workflows (e.g., NAACCR data items, ICD-O-3 histology/topography coding, AJCC staging) is a plus; prior registry experience is not required
- Strong commitment to teaching and disseminating work through writing and speaking engagements, as creating and giving seminars & presentations and authoring manuscripts is an expectation for this position.
- Fluency visualizing data for scientific purposes (e.g., creating figures for manuscripts and presentations)
- Experience and interest in academic research (working with faculty, disseminating work through manuscripts & open-source software, and grant writing)
Not Applicable.
Patient care: We promote health and provide superb clinical care while maintaining our strong tradition of reaching underserved populations and reducing health disparities across North Carolina and beyond.
Education: We prepare tomorrow’s healthcare professionals and biomedical researchers from all backgrounds by facilitating learning within innovative and integrated curricula and team-oriented interprofessional education to ensure a highly skilled workforce.
Research: We develop and support a rich array of outstanding health sciences research programs, centers and resources. We provide infrastructure and opportunities for collaboration among disciplines throughout and beyond our university to support outstanding research. We foster programs in the areas of basic, translational, mechanistic and population research.
- Professional and/or formal educational experience utilizing large language models for research, including deploying, tuning, and optimizing open- and closed-source models in local and cloud environments, including high-security or air-gapped environments for sensitive data
- Experience applying LLMs to structured information extraction from unstructured text (e.g., named entity recognition, relation extraction, schema-constrained or function-calling-based structured output generation)
- Experience with natural language processing utilizing traditional data science approaches (word2Vec, NLTK, Spark NLP, etc.) and/or NLP utilizing large language models
- High level of proficiency in either R or Python in the areas of machine learning, deep learning, statistical analysis, computer vision, and/or graph analysis
- Experience with data engineering to create data science pipelines, deploy and scale models, and maintain and thoroughly document code and models, including designing evaluation frameworks for model/pipeline accuracy (e.g., precision/recall/F1 against gold-standard human annotation
- Knowledge of SQL programming, data modeling, and relational database systems such as Oracle, MS-SQL, MySQL, etc.
- Highly capable of working in a cross-functional team and functioning as lead scientist on research and development efforts – ability to manage multiple projects at once while delivering high-quality work on time
- Strong interest in clinical data and desire to develop deep expertise in EHR and claims data; interest in developing deep expertise in cancer registry data standards and abstraction workflows (e.g., NAACCR data items, ICD-O-3 histology/topography coding, AJCC staging) is a plus; prior registry experience is not required
- Strong commitment to teaching and disseminating work through writing and speaking engagements, as creating and giving seminars & presentations and authoring manuscripts is an expectation for this position.
- Fluency visualizing data for scientific purposes (e.g., creating figures for manuscripts and presentations)
- Experience and interest in academic research (working with faculty, disseminating work through manuscripts & open-source software, and grant writing)
Not Applicable.
Research Data Scientist Jobs by Experience Level
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Find Research Data Scientist JobsResearch Data Scientist Job Market
Who's Hiring
- Google16
- TikTok3
- AIG2
- Apple2
- ConTra2
Top Industries Hiring
- Education
- Insurance
- Technology & Software
- Electronics & Hardware
- Healthcare & Medical Services
What Employers Look For
The qualifications that appear most often in research data scientist jobs.
- PhD or Master's degree in statistics, computer science, machine learning, or a related quantitative field
- Proficiency in Python and experience with ML frameworks such as PyTorch or TensorFlow
- Strong background in statistical modeling, experimental design, and causal inference
- Experience publishing or presenting research findings internally or at academic conferences
- Familiarity with large-scale data processing tools such as Spark or distributed computing environments
- Ability to translate ambiguous research questions into structured, testable hypotheses
Tips for Your Research Data Scientist Job Search
Tailor your resume to research depth
Hiring managers for research roles scan for publications, conference papers, or internal research reports before they look at job titles. List any peer-reviewed work, preprints, or technical blog posts in a dedicated section so reviewers can gauge your independent contribution.
Apply early to roles that fit
Migrate Mate lists research data scientist openings from across the United States in one place, so you can find roles that match and apply directly to each listing.
Quantify model impact, not just accuracy
Research teams care less about hitting a benchmark and more about downstream business or scientific impact. Replace accuracy scores on your resume with outcomes: latency reduction, revenue attribution, or reduction in manual review time driven by a model you built.
Filter openings by methodology keywords
Search using terms like causal inference, Bayesian methods, or reinforcement learning rather than the generic job title alone. Research-oriented postings almost always include the technique in the description, and matching that language signals you read the spec closely.
Prepare a research presentation for the interview
Most research data scientist loops include a 20-to-30-minute deep dive where you walk through a past project. Prepare a slide deck that covers your problem framing, methodology choice, failure modes you encountered, and what you'd do differently, not just the final result.
Negotiate scope before negotiating compensation
Research roles vary widely in publishing freedom, compute budget, and collaboration with product teams. Before discussing compensation in the offer stage, ask directly what percentage of your time goes to long-horizon research versus production deliverables so you're evaluating the full offer.
Research Data Scientist Jobs: Frequently Asked Questions
Which companies are hiring the most research data scientists?
The companies hiring the most research data scientists right now include Google, TikTok, and AIG, with the largest share of openings in California, Ohio, and Illinois, based on current listings on Migrate Mate as of September 2026. Demand is especially concentrated in technology platforms, healthcare analytics firms, and financial services companies with dedicated research divisions.
How many research data scientist jobs are remote?
About 52% of research data scientist openings are fully remote or hybrid as of September 2026, reflecting a strong shift toward flexible arrangements in knowledge-work roles. Sub-areas focused on NLP, applied machine learning research, and statistical consulting tend to have the highest share of fully remote postings compared to roles tied to proprietary data infrastructure or lab environments.
How do you become a research data scientist?
Most research data scientists start with a graduate degree in a quantitative field such as statistics, computer science, or applied mathematics, then build a portfolio of independent research through thesis work, open-source projects, or published papers. Gaining hands-on experience with production ML systems through internships or industry roles strengthens your application, and demonstrating the ability to frame novel problems, not just solve defined ones, is what distinguishes research candidates from applied data scientists.
Can you get a research data scientist job with little experience?
You can enter research data science with limited industry experience if your academic or independent work demonstrates strong research fundamentals. Hiring teams for junior research roles prioritize evidence of rigorous methodology, whether from a thesis, a Kaggle competition writeup with solid experimental design, or a contribution to an open-source research project, over years of job experience. Targeting companies with formal research residency or associate researcher programs gives you a structured path in.
What does the research data scientist interview process look like?
The process typically runs four to six stages: an initial recruiter screen, a technical phone screen covering probability and statistics or coding, a take-home research problem or case study, a research presentation where you walk through past work, a system design or methodology deep-dive with senior researchers, and a cross-functional interview assessing collaboration and communication. Some organizations compress these into a single onsite day while others spread them across multiple weeks.
Where can I find and apply to research data scientist jobs?
You can find and apply to research data scientist jobs on Migrate Mate, which lists current openings from across the United States in one place. Search the listings to find roles that match your background and specialization, then apply directly to each one that fits.
See All 64 Research Data Scientist Jobs
Find roles that match your experience and apply in just a few clicks.
Find Research Data Scientist Jobs