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Senior Data Scientist; AI-assisted Clinical Development

Job in Boston, Suffolk County, Massachusetts, 02298, USA
Listing for: F. Hoffmann-La Roche AG
Full Time position
Listed on 2026-07-14
Job specializations:
  • IT/Tech
    Machine Learning/ ML Engineer, Data Scientist, AI Engineer (Applied/Software), Data Analyst
Salary/Wage Range or Industry Benchmark: 142700 - 264900 USD Yearly USD 142700.00 264900.00 YEAR
Job Description & How to Apply Below
Position: Senior Data Scientist (AI-assisted Clinical Development)

Overview

This role is based in the Innovation Accelerator (IA) team, the innovation engine and connective tissue for Design, Data and Data Science innovation strategy within Product Development Data Sciences (PDD). The IA Senior Data Scientist builds and deploys AI/ML‑powered digital solutions that transform how we develop medicines.

Responsibilities
  • Partner closely with product managers, software engineers, and UX researchers to design, test, and scale statistical capabilities that unlock actionable insights from clinical, operational, and real‑world data.
  • Apply advanced statistical and machine learning methods to support development of tools and software products for evidence generation, trial design, and decision support across R&D initiatives.
  • Act as subject‑matter expert to inform software products for the conduct of simulation studies and comparative evaluations of analytical approaches for clinical and operational scenarios.
  • Collaborate with domain experts to translate scientific problems into data science workflows, identifying patterns of workflows that can be automated and productized.
  • Build and maintain model development pipelines, ensuring traceability, performance monitoring, and reproducibility.
  • Contribute to the integration of models and algorithms into production applications, working closely with engineering and product teams.
  • Participate in the design of compliant and interpretable ML product architectures for clinical development environments.
  • Design documentation templates that communicate modeling decisions, trade‑offs, and performance summaries to cross‑functional stakeholders.
  • Contribute to internal knowledge sharing, peer reviews, and community learning within the data science function.
Qualifications
  • Master’s or PhD in Data Science, Computer Science, Statistics, Applied Mathematics, Bioinformatics, or a related field.
  • 3+ years of experience applying machine learning and statistical modeling to data‑centric problems in research or product environments.
  • Proficient with Python or R, including experience with ML libraries such as scikit‑learn, XGBoost, Tensor Flow, or PyTorch.
  • Experience in experimental design, simulation, and evaluation of model performance.
  • Ability to translate scientific or business questions into model architectures and data pipelines.
  • Practical experience with version control, testing frameworks, and collaborative software development.
  • Experience working with one or more of: RWD/RWE, decision analysis, clinical biomarkers, Bayesian inference, or interpretable ML.
  • Attention to detail, quality work, and ability to manage and prioritize multiple projects simultaneously.
  • Excellent collaboration skills, statistical consulting, interpersonal skills, ability to influence without authority, and build strong collaborative relationships.
  • Capacity for independent thinking and decision making based on sound principles.
  • Excellent strategic agility, problem solving, and critical thinking skills beyond the technical domain.
  • Respect for cultural differences when interacting with colleagues in the global workplace.
  • Excellent verbal and written communication skills, specifically in presentation and writing, explaining complex technical concepts in clear language.
Preferred
  • Experience contributing to ML product pipelines and deployment workflows.
  • Experience building evidence synthesis models (e.g., network meta‑analysis) or constructing data‑driven priors for drug development.
  • Experience with Bayesian computing or probabilistic programming languages (e.g., Stan, PyMC, brms).
  • Experience with collaborative coding practices and modern version control (git, CI/CD).
  • Experience with generative AI tooling for software development or data analysis relevant to the pharmaceutical industry.
  • Knowledge of compliance‑related standards (e.g., GxP, HIPAA).
  • Publication or public presentation experience in applied statistics or machine learning.
  • Experience working in agile, cross‑functional teams with scientific or product stakeholders.
Location

This position is based in Boston, MA. Relocation assistance is not available.

Salary and Benefits

The expected salary range for this position based on the primary location of…

Position Requirements
10+ Years work experience
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