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.
This is your invitation.
Bring your ideas, your grit, and your care for people.
Join us and shape the future of care.
The Opportunity
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.
What you'll do
- 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
What you bring to the table
- 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 can offer you
- 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
Fullscript shares salary ranges to support transparency and help candidates make informed decisions. The range shown reflects base salary only and does not include stock options, wellness stipends, or other benefits that are part of Fullscript’s total rewards package.
Final compensation depends on experience, skills, and location. We review pay regularly to stay aligned with market data and internal equity. Benefits and total rewards may vary by region.
Why Fullscript
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.
What to Know Before You Apply
We’re grateful for the interest in joining Fullscript. To make sure your application reaches our hiring team, please apply directly through our careers page.
A quick note: Due to the high volume of applications, we’re not able to respond to phone or email inquiries about application status. If there’s a match, our team will reach out directly.
Fullscript is an equal opportunity employer committed to creating an inclusive workplace. Accommodations are available upon request at [email protected].
All offers are contingent on successful background checks conducted in compliance with federal, state, and provincial laws.
We use AI tools to support parts of the hiring process, including screening and reviewing responses. Final hiring decisions are always made by people and follow all applicable privacy and employment laws in Canada and the U.S.
Learn More
www.fullscript.com
@fullscriptHQ on instagram
@fullscript on YouTube
FullScript on LinkedIn
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, 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.
