Data Scientist Job at TALENT Software Services, Novato, CA

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  • TALENT Software Services
  • Novato, CA

Job Description

Are you an experienced Data Scientist with a desire to excel? If so, then Talent Software Services may have the job for you! Our client is seeking an experienced Data Scientist to work at their company in Novato, CA.

Position Summary: Client's Data Science is responsible for designing, capturing, analyzing, and presenting data that can drive key decisions for Clinical Development, Medical Affairs, and other business areas of Client. With a quality-by-design culture, Data Science builds quality data that is fit-for-purpose to support statistically sound investigation of critical scientific questions. The Data Science team develops solid analytics that are visually relevant and impactful in supporting key data-driven decisions across Client. The Data Management Science (DMS) group contributes to Data Science by providing complete, correct, and consistent analyzable data at data, data structure and documentation levels following international standards and GCP. The DMS Center of Risk Based Quality Management (RBQM) sub-function is responsible for the implementation of a comprehensive, cross-functional strategy to proactively manage quality risks for clinical trials. Starting at protocol development, the team collaborates to define critical-to-quality factors, design fit-for-purpose quality strategies, and enable ongoing oversight through centralized monitoring and data-driven risk management. The RBQM Data Scientist supports central monitoring and risk-based quality management (RBQM) for clinical trials. This role focuses on implementing and running pre-defined KRIs, QTLs, and other risk metrics using clinical data, with strong emphasis on SAS programming to deliver robust and scalable analytics across multiple studies.

Primary Responsibilities/Accountabilities:

The RBQM Data Scientist may perform a range of the following responsibilities, depending upon the study's complexity and the study's development stage:

  • Implement and maintain pre-defined KRIs, QTLs, and triggers using robust SAS programs/macros across multiple clinical studies.
  • Extract, transform, and integrate data from EDC systems (e.g., RAVE) and other clinical sources into analysis-ready SAS datasets.
  • Run routine and ad-hoc RBQM/central monitoring outputs (tables, listings, data extracts, dashboard feeds) to support signal detection and study review.
  • Perform QC and troubleshooting of SAS code; ensure outputs are accurate and efficient.
  • Maintain clear technical documentation (specifications, validation records, change logs) for all RBQM programs and processes.
  • Collaborate with Central Monitors, Central Statistical Monitors, Data Management, Biostatistics, and Study Operations to understand requirements and ensure correct implementation of RBQM metrics.

Qualifications:

  • PhD, MS, or BA/BS in statistics, biostatistics, computer science, data science, life science, or a related field.
  • Relevant clinical development experience (programming, RBM/RBQM, Data Management), for example:
  • PhD: 3+ years
  • MS: 5+ years
  • BA/BS: 8+ years
  • Advanced SAS programming skills (hard requirement) in a clinical trials environment (Base SAS, Macro, SAS SQL; experience with large, complex clinical datasets).
  • Hands-on experience working with clinical trial data.•Proficiency with Microsoft Word, Excel, and PowerPoint.
  • Technical – Preferred / Strong Plus
  • Experience with RAVE EDC.
  • Awareness or working knowledge of CDISC, CDASH, SDTM standards.
  • Exposure to R, Python, or JavaScript and/or clinical data visualization tools/platforms.

Preferred:

  • Knowledge of GCP, ICH, FDA guidance related to clinical trials and risk-based monitoring.
  • Strong analytical and problem-solving skills; ability to interpret complex data and risk outputs.
  • Effective communication and teamwork skills; comfortable collaborating with cross-functional, global teams.
  • Ability to manage multiple programming tasks and deliver high-quality work in a fast-paced environment.

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