About Promptly
Promptly is building the first patient‐centered global evidence network, offering real‐world data sharing and monetization capabilities. We generate new knowledge from harmonized datasets and patient‐generated data in a secure privacy‐preserving environment. We deliver insights to health systems, payers and life‐science companies across cardiometabolic, oncology and immunology. Operating in 10 countries, we promote better healthcare at lower costs for thousands of patients every day through real‐world evidence.
About The Role
As Medical Data Analyst you will shape and execute Promptly's 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 approaches and reliably extract, structure and analyse data to support research, product development and partner‐facing insights.
Responsibilities
- Develop the RWD analytics roadmap: define priorities and requirements aligned with product and partner needs; translate high‐level objectives into executable workstreams and measurable deliverables.
- Work hands‐on with raw data: query and analyze source tables directly (EHR, claims, registries and partner exports), profile datasets, identify anomalies and build reliable extraction logic.
- Bridge data engineering and analytics: partner closely with ETL 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), emphasizing fit‐for‐purpose analytics and operational scalability.
- Support monetizable evidence products: contribute to packaging datasets and analytical outputs into products (e.g., condition‐specific RWD assets) that are coherent, validated and aligned with partner expectations.
- Stakeholder management and enablement: align internal stakeholders around definitions and metrics; set analytical standards and documentation practices; mentor team members on data reasoning and clinical interpretation.
Qualifications & Skills
- Clinical/medical background (medicine, nursing, pharmacy) or a health‐science background with strong domain understanding (public health, epidemiology, biomedical informatics).
- Strong practical experience with raw healthcare databases: understanding schemas, joins, provenance and common quality issues.
- Proficiency in SQL (complex joins, window functions, performance‐aware querying) mandatory; Python (preferred) or R for data manipulation and analysis.
- Experience with RWD analytics workflows: cohort building, feature engineering, endpoint definition, longitudinal data handling, missingness assessment and bias awareness.
- Strong analytical judgement and communication skills—able to explain technical findings to clinical and non‐technical stakeholders and translate ambiguous questions into concrete specifications.
Preferred Qualifications
- Experience with OMOP CDM (cohort definitions, concept sets, phenotyping) and comfort navigating standardized and non‐standardized data structures.
- Previous experience with AI tools in healthcare data transformation.
- Familiarity with healthcare terminologies (SNOMED CT, LOINC, RxNorm, ICD) and practical implications for mapping and analysis.
- Experience defining and monitoring data quality metrics and implementing repeatable validation checks across datasets/partners.
- Prior experience in outcomes research, epidemiology, pharmacoepidemiology or building analytics assets for life sciences / health systems.
- Exposure to federated or privacy‐preserving analytics constraints and multi‐partner data governance considerations.
Position
- Remote‐first
- Full‐time
What We Offer
- Define and own a strategic global initiative from the ground up
- Shape the future of Promptly's partner ecosystem and data network expansion
Financial Benefits
- Competitive salary
- Annual performance bonus
- Equity compensation via our ESOP (open to all team members)
- Annual training allowance
- Private health insurance
- Home‐office equipment allowance
Non‐Financial Benefits
- Equal opportunity and inclusive environment
- Flexible work schedule and vacation policy
- Corporate events and international team gatherings
Recruiting Process
- Initial Interview — Meet future manager/team members to understand scope.
- Technical & Strategic Assessment — Short case related to partner management or program design.
- Final Interview (if needed) — Deep‐dive discussion to align on expectations and vision.
- Offer Stage — Share the offer and welcome you to the team!
Our Culture & Values
- Empathy — Ownership — Responsibility — Teamwork — Excellence
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