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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.
Job Responsibility
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
Requirements
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
What we offer
Competitive Salary ranges
Remote-first flexibility to work where you work best, with Ottawa, Toronto, or Calgary preferred for this role
Flexible PTO and competitive pay, because work-life balance matters
RRSP/401k match and stock options to invest in your future
Premium benefits package with customizable coverage, paramedical services, and an HSA
Fullscript discounts to save on high-quality wellness products
Continuous learning opportunities to grow your skills and career