Research Data Scientist (Part-time)

Schedule: Part-time; Remote
Payment: Hourly at $40/hour
Start Date: Immediate

About Fit Minded
Fit Minded is a strategic applied science firm for digital health companies, integrating scientific research with business strategy to drive growth, boost revenue, and build credibility. We offer tailored solutions that empower organizations to incorporate science into their operations, ensuring success in a competitive marketplace. Our team comprises experienced professionals dedicated to designing research studies that establish evidence and enhance visibility for our clients. At Fit Minded, we are committed to helping companies grow by integrating science into every aspect of their organization. Learn more at fit-minded.com.

The Work Environment
This isn't an academic biostatistics role, and it isn't a standard industry analytics role either. You will support analyses across multiple client engagements at once. Each client is at a different stage of scientific maturity, works in a different area of digital health, and brings different data structures and business pressures. Product data is messy, samples are rarely what they first appear to be, and the claims clients want to make often outrun what the data can support. You'll context-switch constantly and get up to speed quickly on new datasets without sacrificing rigor.
This role is rooted in our values: Courageous Ownership, Balanced Excellence, Fearless Innovation, and Clear & Accountable. You'll be expected to make sound analytic judgment calls, document them, and move work forward without waiting for complete instructions. We value proactive communication and trust you to problem-solve first, then share your approach.

The Position
We are seeking a Research Data Scientist to serve as the analytic engine behind our science team. Reporting to our Research Scientist Manager, you will partner with our PhD Research Scientists while they lead client engagements. You'll shape study designs for analytic feasibility, build analysis plans, run the analyses, and turn results into accurate, defensible findings.

You won't own client relationships. You will be the person who ensures every claim Fit Minded makes is supported by the data behind it. That means knowing when a pre-post change is clinically meaningful, when an engagement-outcome association is survivorship bias, and when an observational comparison cannot support the conclusion a client wants.

Your onboarding is structured in two stages:

• Months 0–3: Learn Fit Minded's data standards, analytic templates, and reporting workflow under the Research Science Manager. Own defined analyses on active engagements from the start.
• Months 3–6: Own analyses end-to-end across multiple concurrent engagements, from analysis plan through results write-up, with Research Science Manager review on methods decisions.

How You’ll Contribute

• Build analytic samples from product and study data. Apply inclusion criteria, construct cohorts, and document attrition with flow diagrams.
• Characterize engagement and retention with appropriate metrics and distributions, including retention curves and time-to-event analyses of disengagement and response.
• Evaluate change on validated outcome measures using paired tests, effect sizes, reliable change, MCID-based classification, and response and remission rates, with correct handling of baseline severity thresholds.
• Model longitudinal and nested data using mixed-effects models with defensible time coding and random-effects structures. Diagnose missingness and apply multiple imputation with sensitivity analyses.
• Run a priori power and sample size calculations for single-arm, two-arm, and longitudinal designs, with assumptions justified from the literature.
• Pressure-test study designs and research questions with our scientists. Flag confounding, reverse causation, multiplicity, and analytic flexibility before they become problems, and separate confirmatory from exploratory findings.
• Write analysis plans, methods, and results sections that meet CONSORT, STROBE, and TREND standards. Draft claims for investor and payer audiences that accurately reflect what the evidence supports.
• Maintain reproducible workflows using scripted R analyses and version control. Document code and analytic decisions so another analyst can rerun any result end to end.

We need someone who:

• Asks what question an analysis is answering before running it, and says so when the data can't support the claim being asked for.
• Manages competing requests from multiple scientists, sets realistic timelines, and communicates progress without being chased.
• Documents decisions as they make them, not after.
• Moves fast without sacrificing quality. Tight timelines are standard, not exceptions.
• Is socially aware and collaborative. You don't need to be extroverted, but you do need to explain methods clearly to scientists and non-scientists alike.

Minimum Qualifications

• Master's in Biostatistics, Epidemiology, Statistics, Quantitative Psychology, Data Science, or a related field.
• 2+ years of post-degree applied analysis experience on health, clinical, or digital product data in industry, a CRO, a health system, or a research center. Graduate research assistantships do not satisfy this requirement.
• Advanced proficiency in R, including mixed-effects models, multiple imputation, and survival analysis, with scripted workflows under version control (Git).
• Experience analyzing change on validated outcome measures, including clinically meaningful change (RCI, MCID, response and remission).
• Experience conducting a priori power analyses and writing statistical analysis plans.
• Demonstrated ability to communicate analytic results and limitations accurately to non-statisticians.

Preferred Qualifications

• Psychometric validation (CFA, internal consistency, measurement invariance, IRT).
• Person-centered methods (latent class analysis, LCGA, growth mixture modeling).
• Causal inference with observational data (propensity score methods, interrupted time series, difference-in-differences, regression discontinuity).
• Mediation and moderation analysis tied to behavior change models.
• Experience with digital health engagement or event-log data; SQL proficiency.
• Co-authorship on peer-reviewed publications.
• Familiarity with real-world evidence for payer or regulatory audiences.
• Familiarity with AI tools for workflow optimization.

How to Apply
https://fit-minded.com/careers/

About our CEO, Dr. Jennifer Huberty
Dr. Jennifer Huberty is a distinguished behavioral research scientist with over 25 years of experience, serving as a cornerstone between academia, science, and business—a rare and invaluable skill set. She specializes in digital approaches to promote behavior change and enhance well-being, driving science-driven growth and business innovation. Dr. Huberty is the former Head of Science at Calm and the CEO at Fit Minded Inc., and holds academic roles at Arizona State University, and adjunct faculty roles at Mayo Clinic College of Medicine, University of Texas Health San Antonio/Mays Cancer Center, and Banner Health/Univ of Arizona. With over 200 peer-reviewed publications, she is a recognized leader in clinical study design, brand positioning research, and scientific content marketing to support data-driven business strategies. Learn more here.