Senior Data Scientist (AI-assisted Clinical Development)

Roche • Boston, MA

18d • $142,700 - $264,900

About The Position

The Senior Data Scientist is part of the Innovation Accelerator team within Product Development Data Sciences. The team translates long-term strategy into cross-functional innovation use cases, prototypes and helps productize solutions in partnership with internal Roche teams and external collaborators.

This role builds and deploys AI/ML-powered digital solutions to transform medicine development. Working closely with product managers, software engineers, UX researchers, and domain experts, the Senior Data Scientist designs, tests, and scales statistical capabilities that generate actionable insights from clinical, operational, and real-world data. The role applies advanced statistical and machine learning methods to support evidence generation, trial design, and decision support, while helping deliver scalable, ethical, interpretable, and compliant tools for regulated healthcare environments.

The position is based in Boston, Massachusetts. Relocation assistance is not available. The stated expected annual salary range is $142,700–$264,900 USD. Actual pay depends on experience, qualifications, geographic location, and other job-related factors permitted by law. A discretionary annual bonus may be available based on individual and Company performance.

Requirements

• Master’s or PhD in Data Science, Computer Science, Statistics, Applied Mathematics, Bioinformatics, or a related field.
• At least 3 years of experience applying machine learning and statistical modeling to data-centric problems in research or product environments.
• Proficiency in Python or R, including experience with machine-learning libraries such as scikit-learn, XGBoost, TensorFlow, 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 with one or more of the following: real-world data or real-world evidence (RWD/RWE), decision analysis, clinical biomarkers, Bayesian inference, or interpretable machine learning.
• Attention to detail and quality, with the ability to manage and prioritize multiple long- and short-term projects.
• Strong collaboration and statistical consulting skills, including the ability to contribute effectively in cross-functional teams, influence without authority, and build relationships with scientific and non-scientific partners.
• Independent thinking and the ability to make decisions based on sound principles.
• Strategic agility, problem-solving, and critical-thinking skills that extend beyond the technical domain.
• Respect for cultural differences when interacting with colleagues in a global workplace.
• Excellent verbal and written communication, presentation, and writing skills, including the ability to explain complex technical concepts clearly.

Nice To Haves

• Experience contributing to machine-learning product pipelines and deployment workflows.
• Experience building evidence synthesis models, such as network meta-analysis, or constructing data-driven priors for drug development.
• Experience with Bayesian computing or probabilistic programming languages, including Stan, PyMC, or brms.
• Experience with collaborative coding practices and modern version control, such as Git and CI/CD.
• Experience with generative AI tools for software development, such as agentic coding, spec-driven development, or AI code reviews.
• Experience developing agentic AI tools for data analysis or pharmaceutical-industry processes.
• Knowledge of compliance-related standards such as GxP or HIPAA.
• Publication or public-presentation experience in applied statistics or machine learning.
• Experience working in agile, cross-functional teams with scientific or product stakeholders.

Responsibilities

• Apply advanced statistical and machine learning methods to develop tools and software products for evidence generation, trial design, and decision support across R&D initiatives.
• Serve as a subject matter expert for software products used to conduct simulation studies and compare analytical approaches for clinical and operational scenarios.
• Collaborate with domain experts to translate scientific problems into data science workflows and identify workflows that can be automated and productized.
• Build and maintain model development pipelines that support traceability, performance monitoring, and reproducibility.
• Contribute to integrating models and algorithms into production applications in partnership with engineering and product teams.
• Participate in designing compliant and interpretable machine-learning product architectures for clinical development environments.
• Design documentation templates to 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.

Benefits

• A discretionary annual bonus may be available based on individual and Company performance.
• The position qualifies for company benefits detailed at the linked benefits page.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior