Clinical Research Data Analyst (Contract)
Noom GrowthRemote - USPosted 3 April 2026
Tech Stack
Job Description
Noom is on a mission to help people live better, longer. We’re a consumer-led digital health company, connecting people to content, coaching, community, and clinicians, to build lasting habits and live healthier lives. We’re a high-growth organization powered by science, technology, and world-class talent. When you join Noom, on any team, you’ll see the impact of your work on the world.
Our Clinical Research Team
Noom’s Clinical and Research team drives evidence generation and ensures our programs are grounded in rigorous science. We partner cross-functionally across Clinical Operations, Data Science, Product, and Regulatory to deliver high-quality research and insights that support our mission and product innovation.
About the Role
As we continue to grow, we’re seeking a part-time Contract Clinical Research Data Analyst to support clinical data quality and integrity across our research initiatives. In this contract role, you will be responsible for ongoing data review, validation, and cleaning activities, ensuring datasets are accurate, complete, and analysis-ready.
You will work closely with Clinical Research Operations, Data Management, Biostatistics, and external partners to support data workflows across the lifecycle of clinical studies.
You Will
Perform ongoing review of clinical data for completeness, accuracy, and consistency across studies
Generate, track, and resolve data queries in collaboration with study coordinators, sites, and data management teams
Execute manual and automated data validation checks to identify discrepancies, protocol deviations, outliers, and missing data
Ensure datasets meet predefined quality standards prior to analysis and database lock
Support configuration, review, and maintenance of Electronic Data Capture (EDC) systems, including edit checks and case report forms (CRFs)
Conduct data cleaning and reconciliation activities across multiple data sources, including adverse events, concomitant medications, laboratory data, and external vendor datasets
Maintain traceability of data changes and ensure audit readiness
Generate data quality metrics, status reports, and query tracking dashboards
Collaborate cross-functionally with Clinical Operations, Biostatistics, and Regulatory teams to deliver high-quality, analysis-ready datasets
About You
If you’re passionate about advancing clinical research through high-quality data and enjoy working in a fast-paced, collaborative environment, this role may be for you!
You Have
2+ years of experience in clinical data management, clinical data review, or a related role
Bachelor’s degree in Life Sciences, Public Health, Biostatistics, or a related field
Hands-on experience with Electronic Data Capture (EDC) systems (e.g., Medidata Rave, REDCap, or similar)
Experience with cloud-based data engineering and analytics platforms (e.g., Databricks, Looker, Hex)
Strong proficiency in SQL and at least one statistical or programming language (e.g., Python, R).
Strong understanding of clinical trial processes, GCP, and data management best practices
Experience with data cleaning, query management, and reconciliation activities
High attention to detail with strong analytical and problem-solving skills
Ability to manage multiple priorities in a fast-paced environment
Strong communication and cross-functional collaboration skills
What Makes This Job Amazing
Opportunity to directly impact the quality and integrity of Noom’s clinical research
Work with a collaborative, mission-driven, and cross-functional team
Contribute to cutting-edge digital health research in a growing organization
Location and Compensation
This is a part-time contract position (20 hours per week) with an hourly rate of $40–$45/hour.
Please note: Market rates for contract roles can vary depending on factors such as location, experience level, and specific skill set.
This position is fully remote.
More About Noom
Noom is a leading whole-person health platform on a mi ... (truncated, view full listing at source)
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