Clinical Data Scientist – Hybrid or Remote Overview A growing organization in the healthcare and life sciences technology space is seeking a Clinical Data Scientist to support the final stages of its clinical data pipeline. This role focuses on transforming complex clinical datasets into clean, standardized, analysis‑ready deliverables for use in clinical research and regulatory submissions. The ideal candidate is detail‑oriented, technically versatile, and passionate about delivering high‑quality clinical data. You will work closely with cross‑functional teams—including Clinical Operations, Data Platform Engineering, and AI/ML teams—to ensure accuracy, traceability, and compliance across all data outputs. This role may be hybrid or fully remote; candidates in the SF Bay Area are preferred but not required. Key Responsibilities Data Transformation & Delivery Convert raw, manually abstracted, and AI‑processed clinical data into standardized formats (e.g., CDISC SDTM/ADaM) or client‑specific data models. Build analysis‑ready datasets from diverse sources including EMRs, EDC systems, and internal abstraction tools. Statistical Programming & Reporting Develop and generate Tables, Listings, and Figures (TLFs) for clinical study reports and interim analyses using SAS, R, or Python. Data Integrity & Quality Control Perform comprehensive data cleaning and validation checks. Investigate discrepancies to distinguish between true clinical complexity and upstream data errors. Cross‑Team Collaboration Partner with engineering teams to automate data cleaning and validation workflows. Serve as an early tester and internal customer for new data infrastructure tools. Documentation Create and maintain clear documentation including data specifications, derivation logic, reviewers’ guides, and Define.xml to support audits and regulatory submissions. Ad‑Hoc & Exploratory Analysis Support internal and external stakeholders with data queries, one‑off analyses, and insights that demonstrate the value of the platform. Ethical & Compliant Data Management Follow all applicable privacy, security, and compliance requirements (e.g., HIPAA). Promote ethical handling of sensitive clinical data. Qualifications Education BSc or MSc in Statistics, Mathematics, Computer Science, Life Sciences, or a related field. Experience 2–5+ years in clinical data science, statistical programming, or clinical data management within Pharma, Biotech, or related environment. Technical Skills Strong proficiency in SAS, R, Python, and SQL. Familiarity with version control (Git) preferred. Experience with CDISC SDTM/ADaM standards. Understanding of oncology endpoints (e.g., RECIST, survival analysis) and real‑world data (RWD) is a plus. Core Competencies Demonstrated expertise in cleaning and stitching complex datasets. Ability to work with unstructured text or NLP‑derived outputs is highly desirable. Exceptional attention to detail and accuracy. Strong written and verbal communication skills. Self‑directed, curious, humble, and collaborative. Additional Information Travel: Up to 5% Compensation: Competitive salary range based on experience, qualifications, and location. Eligible for equity, annual performance bonus, and comprehensive benefits.
Clinical Data Scientist • Oakland, CA, United States
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