Senior Analytics Engineer, Product

WHO WE ARE Inato is a Tech for Good company striving to bring clinical research to each and every patient, regardless of who they are or where they live. To do this, we are building the world's first clinical trial platform to create greater visibility, access, and engagement across a more diverse population of doctors and their patients. Drug development is a challenging, intellectually complex, and rewarding endeavor: we enable global pharmaceutical companies to confidently partner with community-based researchers to increase patient access to the latest medical innovations. Our AI-powered platform currently offers clinical trials from leading companies to over 5,500 sites across the globe and we are well poised for growth in 2026. We are a growing team of passionate pharmaceutical experts, software and AI engineers, professional services members, and many more—all bringing their unique perspectives to solve the challenges facing clinical research. Inato is the recent recipient of Fast Company’s Most Innovative Companies of 2024, Fierce Healthcare’s Fierce 15, and Built In's Best Places to Work 2025. The Role We're hiring a Senior Analytics Engineer, Product to own how data moves from Inato's platform into the hands of the people who depend on it — our product squads, CS and Marketing teams, sponsors, and sites. You'll enable trusted self-service at scale, prove the value of our new product offerings faster, and ship data products directly into the user experience. You'll report to Alexandre Halley (Data Director) and partner daily with Product squads (PMs, engineers, designers), with regular touchpoints into CS, Marketing, and Sponsor / Site Ops. Our stack includes Segment, Airbyte, Dagster, BigQuery, dbt, Hex, FullStory, and more. What you'll own - Trusted self-service at scale. Own metric definitions, build the semantic layer powering our AI-driven self-service in Hex, and govern what gets exposed so non-data teams can answer their own questions confidently.

• Faster value validation for new offerings. Partner with squads to translate vague operational pains (a CS workflow, a sponsor enablement gap, a prototype idea) into working data assets in days — from real-data prototype to production-grade pipeline.
• Data products in front of users.

• Using AI to scale yourself and the team. Automate the parts of data work that don't need a human in the loop so the team can keep pace as new offerings multiply and Inato grows.

• By 6 months: At least three user-facing dashboards or data streams are live.

• Strong dbt + warehouse modeling skills (we use BigQuery).
• Track record of owning data products end-to-end: definition → ship → measurable adoption.
• A genuine product mindset — you start from the user's problem, not from the SQL.
• Excellent written and verbal communication with non-data stakeholders.
• Comfort navigating ambiguity — you can turn a vague operational pain into a working data asset without a fully-specified ticket.

• Experience building production-grade company dashboards.
• Domain exposure to healthcare, clinical trials, or other regulated industries. Working style You're impact-driven and pragmatic — you instinctively reach for the shortest path to the user's need.

• Base salary range: 65,000€ – 80,000€, plus equity. No individual variable bonus. Why this role, why now Inato is in a phase of rapid growth driven by new product offerings, and the data team is one of the functions directly responsible for proving and scaling that value.

• Showcase advanced Excel expertise with real‑world healthcare data: Build a short case study (1–2 pages) that uses pivot tables, Power Query, and complex formulas (e.g., XLOOKUP, array formulas) to clean, merge, and visualize a sample clinical‑trial dataset. Include screenshots of dashboards and a brief explanation of how your analysis would help product teams prioritize trial sites—attach this as a PDF link in your résumé or portfolio.
• Demonstrate product‑focused analytics thinking: In your cover letter, reference Inato’s mission (“bringing clinical research to every patient”) and outline a concrete metric you would track (e.g., “site activation velocity” or “patient enrollment conversion rate”). Explain the data sources you’d combine (Excel, internal APIs, trial registry feeds) and the statistical or ML techniques you’d apply to surface actionable insights.
• Prepare a mini‑project that mirrors Inato’s pipeline: Pull publicly available trial data (e.g., from ClinicalTrials.gov), import it into Excel, then use Power Pivot or a simple Python script (if you know it) to build a model that predicts site suitability based on specialty, geography, and past enrollment. Upload the notebook or Excel workbook to GitHub and link it in your application; interviewers will look for reproducibility and clear documentation.
• Highlight cross‑functional collaboration experience: Cite specific instances where you partnered with product managers, data scientists, or clinical researchers to translate analytic findings into product features or roadmap decisions. Use quantifiable outcomes (e.g., “reduced time‑to‑site‑selection by 15%”) to illustrate impact—Inato values engineers who can bridge technical analysis and product strategy.
• Negotiate with market‑aware data: Research French senior analytics engineer salaries (e.g., Glassdoor, Hays salary guide) and factor in Inato’s “Tech for Good” positioning, which often includes equity or impact‑based bonuses. When discussing compensation, present a range anchored to your proven analytics ROI (e.g., “My previous work increased enrollment efficiency by 12%, translating to €X cost savings”), showing you understand both the financial and mission‑driven value you bring.