Remote Research Data Scientist Jobs
Remote Research Data Scientist jobs are open across the U.S. in technology, healthcare, finance, and academic research, at remote-first companies and distributed teams ranging from early-career positions to principal researcher roles. Employers hiring remotely right now include Tempus, Swayable, and Lyra Health. Find a role that fits below and apply directly.
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Lyra is transforming mental health care by creating a frictionless experience for members, providers, and employers. We connect companies and their employees to mental health providers, therapy, and coaching programs that work.
We are looking for a self-driven, technical Data Scientist who cares about impact, ownership and innovation. In this role, you will work closely with Lyra’s Data, Product, Engineering, and Clinical teams on AI/ML initiatives that will enhance the experience of mental health patients and providers.
This Data Scientist role can be filled remotely anywhere within the US, as well as locally in our Burlingame, CA headquarters. Please note that remote-based candidates must be physically located within the United States.
Responsibilities
Work closely with Lyra’s Data, Product, Engineering, and other associated teams to enhance the Lyra platform to serve the needs of our providers and clients.
Become an expert in the diverse data sources we collect and partner with data engineers to build pipelines that apply clinical logic to raw data
Extract actionable insights, develop predictive and generative models, and implement rigorous evaluation frameworks to support product iterations
Complete time-sensitive ad hoc data requests for internal and external stakeholders
Qualifications
5+ years of data analysis in an industry setting with a preference for individuals who have experience in product analytics in the AI/ML space and have partnered with engineering and product teams in prior roles.
Experience collaborating with cross-functional stakeholders across technical, business, and (ideally) clinical domains
Demonstrated understanding of statistical applications and methods (experimentation, probabilities, regression). Experience applying hypothesis testing in an industry or research setting.
Experience developing comprehensive analyses using irregular data from disparate sources. Willing to do whatever it takes to clean messy data prior to deriving insights.
Strong SQL proficiency. Experience writing complex queries with multiple schemas and tables. Preference for candidates who have experience creating views.
Graduate-level Statistics coursework with MS in a quantitative field is preferred (statistics, econometrics, biostatistics, quantitative social sciences).
Preferred Qualifications
Interest in public health a plus
Experience with AI/ML R&D, e.g. prompt engineering and RAG
Experience with Python, including cleaning and analyzing data as well as using Python to parse JSON structured data, call APIs, create user-defined functions, and automate.
Annual salary is only one part of an employee’s total compensation package at Lyra. We also offer generous benefits that include:
Comprehensive healthcare coverage (including medical, dental, vision, FSA/HSA, life and disability insurances)
Lyra for Lyrians; coaching and therapy services
Equity in the company through discretionary restricted stock units
Competitive time off with pay policies including vacation, sick days, and company holidays
Paid parental leave
401K with up to 3% matching
Monthly tech allowance
We like to spread joy throughout the year with well-being perks and activities, surprise swag, regular community celebration…and more!
We can’t wait to meet you.
"We are an Equal Opportunity Employer. We do not discriminate on the basis of race, color, religion, sex (including pregnancy), national origin, age, disability, genetic information or any other category protected by law.
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, summarizing interviews, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
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Who's Hiring



What Employers Look For
The qualifications that appear most often in remote 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 Remote Research Data Scientist Job Search
Apply early to remote roles that fit
Migrate Mate lists remote research data scientist openings from across the U.S. in one place, so you can find roles that match your skills and apply directly without sorting through listings mixed with on-site work.
Build a public portfolio of research work
Remote employers can't observe how you work, so they rely on what you've shipped. Publish documented notebooks, reproducible analyses, or research write-ups that show your methodology, not just your conclusions, so hiring managers can evaluate your process before the first screen.
Prove async communication in your application
Remote research teams move through written channels, not hallway conversations. Write your cover letter and any take-home materials with the same clarity you'd bring to an internal research memo, because distributed teams hire researchers who can explain complex findings in writing without back-and-forth.
Highlight distributed tooling in your resume
Call out the specific tools that matter for remote research work: version-controlled experiment tracking, collaborative notebooks, cloud compute environments, and async documentation practices. Remote hiring managers scan for evidence you already work the way their team does.
Remote Research Data Scientist Jobs: Frequently Asked Questions
How do I get a remote research data scientist job?
Target companies that run distributed research teams, including remote-first tech firms, biotech companies with no central lab mandate, and data-heavy SaaS businesses. Remote employers screen heavily for self-direction, clear async written communication, and the ability to frame research questions independently. Candidates who show reproducible work, documented methodology, and experience presenting findings to non-technical stakeholders in writing consistently stand out.
Which companies hire remote research data scientists?
Remote research data scientist roles are posted by Tempus, Swayable, and Lyra Health and others right now, based on current remote listings on Migrate Mate as of August 2026. Hiring tends to concentrate at remote-first technology companies, distributed healthcare and life sciences organizations, and fintech firms where research work happens entirely in cloud-based environments.
Can you get a remote research data scientist job with no experience?
Yes, but remote entry-level research data scientist roles are harder to land because employers expect you to work independently from day one without in-person mentorship. Smaller remote-first startups and research-oriented nonprofits are more open to candidates without a full professional history. A portfolio of self-directed projects, public notebooks, or contributed research code can substitute effectively for direct work experience.
Do you need a degree for remote research data scientist jobs?
Usually, but the field is moving. Most remote research data scientist postings still prefer a graduate degree in statistics, computer science, or a related quantitative field, particularly for roles involving original research design. Remote employers weigh demonstrated research output, published or public work, and measurable modeling results heavily alongside formal credentials, so a strong portfolio can offset a non-traditional educational background.
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