Data Science Researcher Jobs
Data Science Researcher jobs are open across technology, healthcare, finance, and academia, from new-grad and junior levels up to principal and staff, with specializations in machine learning research, statistical modeling, and natural language processing. Scan the live roles below and apply to whichever ones fit.
Find Data Science Researcher JobsOverview
Showing 5 of 46+ Data Science Researcher jobs
Domicile Information: This is a hybrid position located in Memphis, TN; Plano, TX; or Pittsburgh, PA. Candidates must live within 50 miles of the campus location. Employees will be required to work at the FedEx campus location several times per week.
Business Summary
The Manager of Data Science and Operations Research (DSOR) is a crucial leadership position responsible for enabling value creation through the application of Data Science and Operations Research methodologies. This support role requires a blend of strategic business thinking, product design, project management, user empathy, ability to structure the work with stakeholders, and proactive communication of progress or challenges. The Manager will closely partner and support a team of DSOR practitioners, fostering a culture of curiosity, rapid experimentation, and continuous improvement. This position is pivotal in translating business ideas into actionable solutions, ensuring progress through strategic enablement support, design excellence, and championing the use of the scientific method across the enterprise.
Essential Functions
- Builds and promotes advanced analytics and data science capabilities, to extract insights from vast data resources and inform decision-making across the business.
- Hiring, coaching, performance management, and strategic planning, as well as staying current with the latest developments in data science and collaborating with IT and business leadership on advanced analytics initiatives.
- Advanced Quantitative Background: Master’s or Ph.D. in Computer Science, Operations Research, Data Science, Machine Learning, Artificial Intelligence, Statistics, or another quantitative and computational field.
- Strategic AI & ML Leadership: Proven track record of leading and scaling high-performing data science teams to design and deliver advanced machine learning, predictive analytics, and generative AI solutions that drive measurable business value.
- ML Strategy & Experimental Oversight: Direct experience defining the strategic machine learning approach for complex business problems. Proven ability to guide teams through robust feature engineering, experimental design, and model development, while establishing metrics to rigorously measure and ensure model performance, accuracy, and business impact.
- Scientific Method & Experimental Rigor: Strong mastery of the scientific method; proficiency and comfort guiding teams through rigorous hypothesis definition, rapid prototyping, and structured experimentation.
- Opportunity Mobilization: Proven ability to mobilize cross-functional teams to explore new opportunities, foster innovation, and drive continuous experimentation.
- User-Centric Product Vision: Ability to envision and actively contribute to the design of user-centric products that seamlessly integrate data science to drive tangible business value and user engagement.
- Pragmatic & Business-Aligned Decision Making: Strong business acumen with an "engineering" mentality—capable of making pragmatic, rapid trade-offs between model complexity, development velocity, and business impact.
- Modern Software Best Practices: Experience championing high standards for code quality, collaborative workflows (Git-based version control), and reusable, production-ready data science repositories.
- Deep Analytical Empathy:
- Solid theoretical grounding in the mathematical and statistical core of data science to effectively evaluate team methodologies.
- Ability to critically review and guide the application of advanced modeling, deep learning, or neural network architectures.
- MLOps & Lifecycle Advocacy: Strong conceptual understanding of DevOps, MLOps, and LLMOps practices(CI/CD, model monitoring, and automated pipelines) to support the seamless transition of your team's models into production environments.
- Oversee the organization and strategic management of a portfolio of diverse DSOR projects. Ensure clear milestones are defined, progress is tracked systematically, and high-quality deliverables are met on time.
- Govern incoming business demand, set clear priorities, manage team capacity, and establish strict accountability for project progress.
MINIMUM EDUCATION
Bachelor’s degree or equivalent in Data Science, Operations Research, Engineering, Business Administration, Business Analytics, or related discipline. [Advanced degree preferred.]
MINIMUM EXPERIENCE
Five to eight (5 - 8) years of experience in working with teams in analytics, data science, operations research, engineering or a related field, with demonstrated leadership in managing teams and executing August 21, 2024 Version: 2 Page 3 of 3 complex projects. Practitioner or practitioner-adjacent experience in analytics, data science, operations research, or a related fields inclusive of prototyping and rapid experimentation.
Preferred Qualifications:  
Pay Transparency:   
Pay: Plano aand Pittsburgh: $10,231.53/mo to $13,812.57/mo; Memphis: $9,719.96/mo to $13,121.94/mo
Additional Details: Application Criteria: Upload current copy of Resume (Microsoft Word or PDF format only) and answer job screening questionnaire.
For details on our comprehensive benefits, click here.
Federal Express Corporation is an Equal Opportunity Employer including, Vets/Disability.
Reasonable accommodations are available for qualified individuals with disabilities throughout the application process. Applicants who require reasonable accommodations in the application or hiring process should contact recruitmentsupport@fedex.com.
Applicants have rights under Federal Employment Laws:
- Know Your Rights
- Pay Transparency
- Family and Medical Leave Act (FMLA)
- Employee Polygraph Protection Act
E-Verify Program Participant: Federal Express Corporation participates in the Department of Homeland Security U.S. Citizenship and Immigration Services’ E-Verify program (For U.S. applicants and employees only). Please click below to learn more about the E-Verify program:
- E-Verify Notice (bilingual)
- Right to Work Notice (English) / (Spanish)
Domicile Information: This is a hybrid position located in Memphis, TN; Plano, TX; or Pittsburgh, PA. Candidates must live within 50 miles of the campus location. Employees will be required to work at the FedEx campus location several times per week.
Business Summary
The Manager of Data Science and Operations Research (DSOR) is a crucial leadership position responsible for enabling value creation through the application of Data Science and Operations Research methodologies. This support role requires a blend of strategic business thinking, product design, project management, user empathy, ability to structure the work with stakeholders, and proactive communication of progress or challenges. The Manager will closely partner and support a team of DSOR practitioners, fostering a culture of curiosity, rapid experimentation, and continuous improvement. This position is pivotal in translating business ideas into actionable solutions, ensuring progress through strategic enablement support, design excellence, and championing the use of the scientific method across the enterprise.
Essential Functions
- Builds and promotes advanced analytics and data science capabilities, to extract insights from vast data resources and inform decision-making across the business.
- Hiring, coaching, performance management, and strategic planning, as well as staying current with the latest developments in data science and collaborating with IT and business leadership on advanced analytics initiatives.
- Advanced Quantitative Background: Master’s or Ph.D. in Computer Science, Operations Research, Data Science, Machine Learning, Artificial Intelligence, Statistics, or another quantitative and computational field.
- Strategic AI & ML Leadership: Proven track record of leading and scaling high-performing data science teams to design and deliver advanced machine learning, predictive analytics, and generative AI solutions that drive measurable business value.
- ML Strategy & Experimental Oversight: Direct experience defining the strategic machine learning approach for complex business problems. Proven ability to guide teams through robust feature engineering, experimental design, and model development, while establishing metrics to rigorously measure and ensure model performance, accuracy, and business impact.
- Scientific Method & Experimental Rigor: Strong mastery of the scientific method; proficiency and comfort guiding teams through rigorous hypothesis definition, rapid prototyping, and structured experimentation.
- Opportunity Mobilization: Proven ability to mobilize cross-functional teams to explore new opportunities, foster innovation, and drive continuous experimentation.
- User-Centric Product Vision: Ability to envision and actively contribute to the design of user-centric products that seamlessly integrate data science to drive tangible business value and user engagement.
- Pragmatic & Business-Aligned Decision Making: Strong business acumen with an "engineering" mentality—capable of making pragmatic, rapid trade-offs between model complexity, development velocity, and business impact.
- Modern Software Best Practices: Experience championing high standards for code quality, collaborative workflows (Git-based version control), and reusable, production-ready data science repositories.
- Deep Analytical Empathy:
- Solid theoretical grounding in the mathematical and statistical core of data science to effectively evaluate team methodologies.
- Ability to critically review and guide the application of advanced modeling, deep learning, or neural network architectures.
- MLOps & Lifecycle Advocacy: Strong conceptual understanding of DevOps, MLOps, and LLMOps practices(CI/CD, model monitoring, and automated pipelines) to support the seamless transition of your team's models into production environments.
- Oversee the organization and strategic management of a portfolio of diverse DSOR projects. Ensure clear milestones are defined, progress is tracked systematically, and high-quality deliverables are met on time.
- Govern incoming business demand, set clear priorities, manage team capacity, and establish strict accountability for project progress.
MINIMUM EDUCATION
Bachelor’s degree or equivalent in Data Science, Operations Research, Engineering, Business Administration, Business Analytics, or related discipline. [Advanced degree preferred.]
MINIMUM EXPERIENCE
Five to eight (5 - 8) years of experience in working with teams in analytics, data science, operations research, engineering or a related field, with demonstrated leadership in managing teams and executing August 21, 2024 Version: 2 Page 3 of 3 complex projects. Practitioner or practitioner-adjacent experience in analytics, data science, operations research, or a related fields inclusive of prototyping and rapid experimentation.
Preferred Qualifications:  
Pay Transparency:   
Pay: Plano aand Pittsburgh: $10,231.53/mo to $13,812.57/mo; Memphis: $9,719.96/mo to $13,121.94/mo
Additional Details: Application Criteria: Upload current copy of Resume (Microsoft Word or PDF format only) and answer job screening questionnaire.
For details on our comprehensive benefits, click here.
Federal Express Corporation is an Equal Opportunity Employer including, Vets/Disability.
Reasonable accommodations are available for qualified individuals with disabilities throughout the application process. Applicants who require reasonable accommodations in the application or hiring process should contact recruitmentsupport@fedex.com.
Applicants have rights under Federal Employment Laws:
- Know Your Rights
- Pay Transparency
- Family and Medical Leave Act (FMLA)
- Employee Polygraph Protection Act
E-Verify Program Participant: Federal Express Corporation participates in the Department of Homeland Security U.S. Citizenship and Immigration Services’ E-Verify program (For U.S. applicants and employees only). Please click below to learn more about the E-Verify program:
- E-Verify Notice (bilingual)
- Right to Work Notice (English) / (Spanish)
Data Science Researcher Jobs by Experience Level
See All 46 Data Science Researcher Jobs
Find roles that match your experience and apply in just a few clicks.
Find Data Science Researcher JobsData Science Researcher Job Market
Who's Hiring
Top Industries Hiring
- Education
- Consulting & Professional Services
What Employers Look For
The qualifications that appear most often in data science researcher jobs.
- Advanced degree in statistics, computer science, mathematics, or a closely related quantitative field
- Proficiency in Python and R for statistical modeling, experimentation, and data manipulation
- Experience designing and running A/B tests or other controlled experiments at scale
- Hands-on work with machine learning frameworks such as PyTorch, TensorFlow, or scikit-learn
- Ability to communicate research findings clearly to both technical and non-technical audiences
- Familiarity with SQL and distributed computing tools for large-scale data processing and analysis
Tips for Your Data Science Researcher Job Search
Tailor your resume to research outputs
Hiring panels for data science researcher roles scan for published papers, conference presentations, and reproducible experiments. List any arXiv preprints, NeurIPS or ICML submissions, or internal research reports by name so reviewers can verify your contributions independently.
Build a public research portfolio fast
Host annotated notebooks or write-ups that show your full experimental pipeline, from hypothesis through evaluation. Reviewers move quickly, so each project page should open with the research question and your key finding in two sentences or fewer.
Apply early to roles that fit
Migrate Mate lists data science researcher openings from across the United States in one place, so you can find roles that match and apply directly to each listing.
Filter postings by research methodology
Job titles vary wildly across employers, so search by method keywords like 'causal inference,' 'Bayesian modeling,' or 'reinforcement learning' rather than title alone. This surfaces niche teams that post under data scientist, applied scientist, or research engineer.
Prepare a research talk for technical screens
Many data science researcher interviews include a 20-to-30-minute paper presentation or project deep-dive. Practice explaining your methodology and design choices to a non-specialist, since cross-functional stakeholders often sit in on these rounds.
Negotiate scope before negotiating compensation
Research roles differ significantly in publication freedom, compute budget, and collaboration with product teams. Clarifying those parameters during the offer stage lets you evaluate fit beyond title and pay, and signals seniority to hiring managers.
Data Science Researcher Jobs: Frequently Asked Questions
Which companies are hiring the most data science researchers?
The most active employers for data science researchers right now are Johns Hopkins University, Intuit, and Virginia Tech, and the most openings are in California, Texas, and Virginia, based on current listings on Migrate Mate as of November 2026. Demand is especially concentrated at technology companies, academic medical centers, and financial services firms with dedicated research functions.
How many data science researcher jobs are remote?
About 77% of data science researcher openings are fully remote or hybrid as of November 2026, reflecting the role's heavy reliance on code and written output over in-person collaboration. Sub-areas like natural language processing and statistical modeling research tend to have the highest remote share, while positions tied to proprietary hardware or clinical data often require on-site presence.
How do you become a data science researcher?
Most data science researchers start by earning a graduate degree in a quantitative field, then building a public record of research through coursework projects, open-source contributions, or published papers. Applying to research internships at technology companies or national laboratories gives you production-scale experience that academic programs alone rarely provide. After that, targeting roles at organizations with dedicated research teams accelerates your growth faster than generalist data science positions.
How do you get hired as a data science researcher with little experience?
Employers evaluating early-career candidates weigh demonstrated research curiosity over years on the job, so publishing a well-documented replication study or contributing to an open-source research codebase carries real weight. Applying to research engineering or junior scientist roles at mid-size companies is often more practical than targeting large research labs, which typically require a publication record. Reaching out directly to researchers whose work you can cite shows initiative that generic applications rarely convey.
What does the data science researcher interview process look like?
A typical process starts with a recruiter screen focused on your background and research interests, followed by a take-home or live coding assessment testing statistical reasoning and Python fluency. The core round usually includes a research presentation where you walk through a past project in depth, plus a whiteboard or discussion session on experimental design and modeling tradeoffs. Final rounds often add a cross-functional conversation with product or engineering partners who will work directly with your research outputs.
Where can I find and apply to data science researcher jobs?
You can find and apply to data science researcher jobs on Migrate Mate, which lists current openings from across the United States. Search the roles available, find the ones that match your background and research focus, and apply directly to each listing that fits.
See All 46 Data Science Researcher Jobs
Find roles that match your experience and apply in just a few clicks.
Find Data Science Researcher Jobs