Medical Data Analyst

Promptly is building the first patient-centered global evidence network, offering real world data sharing and monetization capabilities. Together with a selected network of Partners, we generate new knowledge from harmonized datasets, augmented with the collection of longitudinal patient‑reported data and patient‑generated digital biomarkers within a secure and privacy‑preserving environment.

We answer the question – is this patient treatment the best it could possibly be?

What’s our purpose

We exist to empower every patient and every health organization on the planet with evidence on the outcomes of care!

Why do we get up in the morning? Well, most healthcare professionals have chosen to work in healthcare driven by their desire to make a difference in patients’ lives. And so have we! We have chosen to follow this calling by addressing the biggest problem in healthcare: the lack of real‑world evidence on the outcomes of care.

For us, society denying patients better care due to lack of access to data is unethical, in a world where technology improved so many aspects of our world. Making the right evidence available to healthcare organizations to help prevent one lost life, one care complication, one failed treatment is the moral obligation that big tech companies have – it’s our Hippocratic Oath.

At Promptly, everything we do is driven by our core purpose: to promote better healthcare at lower costs for patients every day, by making health outcomes available.

As Medical Data Analyst, you will be responsible for shaping and executing Promptly’s real‑world data (RWD) analytics strategy—turning raw healthcare databases into decision‑ready evidence products. You will work across clinical, product, and engineering teams to define analytical priorities, design scalable analytical approaches, and ensure we can reliably extract, structure, and analyse data from diverse sources (OMOP CDM and non‑OMOP) to support research, product development, and partner‑facing insights.

This role is ideal for a clinically grounded professional who is equally comfortable with hands‑on data analysis and higher‑level analytical strategy.

• Develop the RWD analytics roadmap
  : define analytical priorities and requirements aligned with product and partner needs; translate high‑level objectives into executable work streams and measurable deliverables.
• Work hands‑on with raw data
  : query and analyze source tables directly (EHR/claims/registries and other partner exports), profile datasets, identify anomalies, and build reliable extraction logic for downstream analyses.
• Bridge data engineering and analytics
  : partner closely with ETL/data engineering teams to ensure analytical usability of datasets—data quality, lineage, join logic, cohort‑building feasibility, and performance considerations.
• Lead cohort and feature development
  : design cohort definitions, phenotypes, concept sets, and reusable feature libraries; define endpoints, covariates, and derived variables that are robust across data partners.
• Develop scalable analytics workflows
  : standardize repeatable pipelines (SQL + R/Python), implement quality checks, and define best practices for reproducible analytics in version‑controlled environments.
• Deliver insight generation and interpretation
  : produce exploratory analyses, dashboards/metrics, and evidence summaries; interpret findings with clinical and analytical rigor, clearly communicating limitations and data constraints.
• Guide methodological choices pragmatically
  : apply appropriate statistical methods when needed (descriptive epidemiology, modelling, time‑to‑event, confounding mitigation), with an emphasis on fit‑for‑purpose analytics and operational scalability.
• Support monetizable…