Job Details

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.