Clinical Data Insights Analyst
Cluepoints
Company Description
At CluePoints, we’re redefining how clinical trials are run. As the premier provider of Risk-Based Quality Management (RBQM) and Data Quality Oversight software, we harness advanced statistics, artificial intelligence, and machine learning to ensure the quality, accuracy, and integrity of clinical trial data, helping life sciences organizations bring safer, more effective treatments to patients faster.
We’re proud to be an ambitious, fast-growing technology scale-up with a dynamic and diverse international team representing more than 20 nationalities. Collaboration, flexibility, and continuous learning are part of our DNA.
At CluePoints, you’ll find a culture where you can grow, make an impact, and have fun along the way. Guided by our values of Care, Passion, and Smart Disruption, we’re united by a shared mission: to create smarter ways to run efficient clinical trials and deliver AI-powered insights that improve human outcomes worldwide.
The Role
you will drive high-impact clinical and product insights from CluePoints platform data by combining strong analytics, excellent BI/visualization, and scalable data engineering on Databricks. Use AI tools end-to-end to accelerate delivery (documentation, SQL/Python development, QA, and stakeholder-ready narratives) with rigorous validation. Apply statistics and use AI/ML methods when appropriate to enhance insight generation.
- Master’s degree in a quantitative field (statistics, mathematics, engineering, data science, medical sciences, etc.) or equivalent experience.
- 5+ years of experience in a clinical research / clinical data environment.
- StrongSQL and Pythonskills (R optional) for data wrangling, validation, and analytics.
- Strong understanding ofclinical trials and clinical data, with the ability to translate domain context into correct metrics and interpretations.
- StrongBI/visualizationexperience (Power BI/Tableau/Spotfire or equivalent), including dashboard design for different audiences and performance optimization.
- Practical experience usingAI to accelerate analytics delivery(documentation, code scaffolding, QA generation, summaries) with critical review and validation habits.
- Databricks(preferred) or equivalent modern data platform experience; familiarity with Spark/Delta concepts is a plus.
- Excellent English written and oral communication skills.
- Experience inexternal scientific/industry communication (e.g., contributing to a peer-reviewed publication and/or conference presentation; writing industry articles/white papers)is a plus.
- Experience applying ML methods in analytics projectsis a plus.
Insights, BI & stakeholder outcomes
- Explore and analyze CluePoints production platform data to understandusage, value delivered, operational patterns.
- Translate business questions into KPIs, metrics, and insight narratives; recommend actions tailored to stakeholders.
- Design and deliver dashboards and self-service analytics for both exploratory and actionable use cases.
- Apply data storytelling best practices (structure, narrative, takeaway-driven design) to drive adoption.
- Maintain a governed KPIcatalog/ semantic layer (definitions, calculation logic, documentation) to ensure consistent metrics across customers, dashboards, and internalreporting.
- Use AI tools responsibly to accelerate the analytics lifecycle (documentation, SQL/Python scaffolding, QA checks, summaries), with rigorousvalidation.
- Train and mentor customers and colleagues; iterate based on feedback to increase usage and impact.
Data engineering
- Own end-to-end Databricks pipelines and curated datasets (design, build, run, monitor, and test), leveraging experts whenneeded.
- Implement performance and reliability best practices, including monitoring and data quality controls.
Methods & thought leadership
- Select and apply the best analytical approach to answer the business question—statistics or AI/ML—and communicate assumptions, limitations, and conclusions clearly.
- Contribute when relevanttoCluePoints’ external visibility through use cases and scientific materials.