Senior Data Scientist (AI-assisted Clinical Development)

F. Hoffmann-La Roche AG; Boston (MA); On-site; USD 142,700 - 264,900; Full time

Job summary

Genentech in Boston, MA seeks an IA Senior Data Scientist to build and deploy AI/ML-powered digital solutions that transform drug development. You will partner with product managers, software engineers, and UX researchers to design scalable statistical capabilities from clinical, operational, and real-world data.

You will apply advanced ML methods to support evidence generation, trial design, and decision support across R&D, while translating scientific questions into data pipelines and

Qualifications

• Master’s or PhD in Data Science, CS, Stats, applied mathematics, bioinformatics, or related field.
• 3+ years applying ML and statistical modeling to data-centric problems in research or product environments.
• Proficient with Python or R, including ML 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 working with 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 and ability to influence without authority.

Responsibilities

• Partner with product managers, software engineers, and UX researchers to design, test, and scale statistical capabilities from diverse data.
• Apply ML methods to support tools for evidence generation, trial design, and decision support across R&D.
• Inform software products for simulation studies and evaluations of analytical approaches.
• Translate scientific problems into data science workflows and identify automatable patterns.
• Build and maintain model development pipelines with traceability and reproducibility.
• Integrate models and algorithms into production applications with engineering teams.
• Design compliant and interpretable ML architectures for clinical development environments.
• Create templates communicating modeling decisions, trade-offs, and performance to stakeholders.
• Contribute to internal knowledge sharing and peer reviews within the data science function.

Skills

Statistical modeling

Machine learning

Data analysis

Collaboration

Education

Master’s or PhD in Data Science or related field

Tools

Python

R

scikit-learn

XGBoost

TensorFlow

PyTorch

Job description

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, 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 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 Boston, Massachusetts is $142,700 – $264,900 USD annually. Actual pay will be determined based 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. This position also qualifies for the benefits detailed at the link provided below.

Equal Opportunity and EEO Statement

Genentech is an equal opportunity employer. It is our policy and practice to employ, promote, and otherwise treat any and all employees and applicants on the basis of merit, qualifications, and competence. The company’s policy prohibits unlawful discrimination, including but not limited to discrimination on the basis of protected veteran status, individuals with disabilities status, and consistent with all federal, state, or local laws. If you have a disability and need an accommodation in relation to the online application process, please contact us by completing this form Accommodations for Applicants.