Lead Data Scientist

About Fullscript

We’re an industry-leading health technology company on a mission to help people get better. We started in 2011 with one simple idea. Make it easier for practitioners to access the products they trust so they can deliver better care. That simple idea grew into a platform that powers every part of care. Today, more than 125,000 practitioners use Fullscript for clinical insights, lab interpretations, patient analytics, education, and access to high-quality supplements.

Over 10 million patients rely on Fullscript to stay connected to their care plans and follow through on treatment. We build tools that make care smarter and more human. Tools that save time, simplify decisions, and help practitioners stay closely connected to the people they care for. When everything they need is in one place, they can focus on what matters most: helping people get better.

Bring your ideas, your grit, and your care for people. Join us and shape the future of care. We’re hiring a Lead Data Scientist to anchor one of the most important bets in our next chapter. Fullscript is building intelligence trained on real-world functional outcomes. Not textbook data. Not controlled trials. Real longitudinal practitioner data layered with our own prescribing and lab history.

The hard part isn’t building models. It’s designing research that can credibly claim causality in messy, non-randomized healthcare data. Can we say that Protocol X led to Outcome Y, and stand behind it with confidence? You’ll define how we approach causal research, set the methodological standard, and turn complex clinical data into insight the business can actually use. The output of this role will shape product direction, influence executive decisions, and determine whether this initiative becomes foundational to the company’s future.

This is a high bar. We’re looking for someone who’s comfortable owning it.

• Designing rigorous observational research frameworks that move beyond correlation toward defensible causal inference
• Addressing confounding, selection bias, missingness, and other structural challenges in real‑world healthcare data
• Extracting outcome intelligence from newly acquired longitudinal practitioner datasets
• Connecting prescribing patterns, lab data, and behavioral signals into coherent analytical narratives
• Establishing methodological standards that protect the integrity of our claims
• Translating complex statistical findings into clear implications for Product, Marketing, and executive stakeholders
• Leading and mentoring a small data team while remaining deeply hands‑on in research and modeling
• Building repeatable research processes that can scale as new data flows in

• Advanced training in statistics, biostatistics, econometrics, or a related field with deep expertise in causal inference
• Demonstrated experience designing studies in observational healthcare data where randomization is not available
• Practical understanding of the pitfalls in real‑world clinical datasets, including confounding variables, selection effects, and incomplete outcome signals
• Comfort working with messy inputs such as PDF labs, narrative notes, inconsistent schemas, and evolving data structures
• Strong Python proficiency and hands‑on experience with statistical modeling libraries
• A track record of translating analytical insight into tangible business or product decisions
• Professional maturity and autonomy to run a high‑visibility research function independently
• Experience leading or mentoring other data professionals while maintaining technical depth

• Generous PTO and competitive pay
• Fullscript’s RRSP match program for financial health
• Flexible benefits package and workplace wellness program
• Training budget and company‑wide learning initiatives
• Discount on Fullscript catalog of products
• Ability to work wherever you work well

Great work happens when people feel supported, trusted, and inspired. At Fullscript, we stay curious and keep finding smarter ways to make care better. We grow together, take on new challenges, and focus on impact. We put people first, work as a team, and leave egos at the door.