Data Scientist

We are seeking a Clinical Data Scientist to help transform complex clinical and real-world healthcare data into high-quality, analysis-ready datasets that support clinical development, regulatory reporting, and real-world evidence initiatives.

This role sits at the intersection of clinical research, data science, and statistical programming. You'll work extensively in R, partnering with Clinical Operations, Biostatistics, Data Engineering, and AI teams to clean, validate, structure, and deliver reliable datasets used throughout the clinical development lifecycle.

The ideal candidate enjoys solving messy data problems, has exceptional attention to detail, and is passionate about building scalable, reproducible data workflows within a fast-paced environment.

• Build and maintain analysis-ready clinical datasets from multiple sources including EHRs, EDC systems, manual abstraction teams, AI-assisted workflows, and external data providers.
• Clean, transform, validate, and standardize complex clinical datasets using R and SQL.
• Develop reproducible data pipelines and validation workflows to ensure data quality, integrity, and traceability.
• Perform comprehensive QC including identifying missing data, inconsistencies, outliers, and data anomalies.
• Investigate data issues and distinguish between upstream data problems and legitimate clinical findings.
• Collaborate closely with Clinical Operations, Biostatistics, Data Engineering, and AI teams to improve data quality and automation.
• Support creation of analysis datasets and reporting outputs for clinical studies and real-world evidence projects.
• Contribute to documentation including data specifications, derivation logic, validation documentation, and data dictionaries.
• Support regulatory-quality deliverables and maintain compliance with GCP, HIPAA, and internal quality standards.
• Help improve internal tooling, automation, and reusable R workflows across the organization.

• Bachelor's or Master's degree in Statistics, Biostatistics, Computer Science, Mathematics, Life Sciences, or a related quantitative field.

• 3+ years of experience working with clinical trial data, real-world data (RWD/RWE), or healthcare datasets in pharma, biotech, CRO, or healthcare organizations.
• Experience building analysis-ready datasets from complex, multi-source clinical data.

• Advanced R programming experience (required), including daily use in production environments.
• Strong experience with tidyverse (dplyr, tidyr, ggplot2) and reproducible R workflows.
• Experience with SQL for querying and integrating large datasets.
• Python experience is a plus.
• Experience with Git or other version control systems preferred.
• Experience with Shiny, Posit, pharmaverse, or other modern R ecosystem tools is highly desirable.

• Experience working with messy clinical, EHR, EMR, or real-world datasets
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• Strong understanding of data cleaning, validation, QC, and data integrity best practices.
• Familiarity with clinical trial workflows and clinical research data.
• Experience with CDISC standards (SDTM, ADaM) is preferred.
• Experience generating or supporting Tables, Listings, and Figures (TLFs) is a plus.
• Oncology clinical trial or oncology real-world data experience is beneficial but not required.

• Strong analytical and problem-solving skills.
• Exceptional attention to detail and commitment to data quality.
• Comfortable working with ambiguity and evolving priorities in a fast-paced environment.
• Clear communicator who can explain technical decisions to both technical and non-technical stakeholders.
• Self-directed, collaborative, and eager to improve processes through automation and continuous improvement.