Principal Data Scientist (AI-assisted Clinical Development)

F. Hoffmann-La Roche AG; Boston (MA); On-site; USD 169,100 - 314,000; Full time

Job summary

F. Hoffmann-La Roche AG is seeking an experienced Data Scientist to design and deploy AI/ML powered digital solutions for clinical development and decision support.

You will collaborate with product managers, software engineers, and UX researchers to scale statistical capabilities across real-world data in regulated healthcare environments. The role emphasizes strong product-thinking, deep technical fluency in Python/R, and a track record of translating complex questions into robust ML models.

Qualifications

• Advanced degree in data science or related field.
• 6+ years applying statistics and ML in biomedical or digital health domains.
• Proven model development and decision-support experience.
• Proficient in Python or R and ML libraries (scikit-learn, TensorFlow, PyTorch).
• Production ML pipelines experience for training, evaluation, and deployment.
• Experience with real-world data, Bayesian methods, causal inference.

Responsibilities

• Develop and apply advanced statistics and ML for clinical tools.
• Design simulation studies for evaluating innovative trial designs.
• Translate domain questions into software requirements for models.
• Lead exploratory analysis of clinical, biomarker, and operational data.
• Build scalable pipelines for data processing, model training and deployment.
• Ensure fairness and mitigate bias in deployed algorithms.
• Co-lead ML/GenAI system architecture with traceability and explainability.
• Collaborate with software, product, UX, and science teams to integrate models.
• Publish and present novel methodologies in internal/external venues.
• Promote best practices for statistical modeling and responsible AI.

Skills

Python

R

ML libraries

Bayesian methods

Data visualization

Cross-functional collaboration

Education

Master’s or PhD in Data Science

Tools

TensorFlow

PyTorch

scikit-learn

Job description

Opportunity

A healthier future. It’s what drives us to innovate. To continuously advance science and ensure everyone has access to the healthcare they need today and for generations to come. Creating a world where we all have more time with the people we love. That’s what makes us Roche. 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). We translate our long‑term PDD vision into actionable strategy, shaping and prioritizing innovative cross‑functional use cases that span PDD, PD, and Pharma. As both integrators and incubators, we explore, prototype, and help productize solutions to deliver impact in close partnership with internal Roche teams and external collaborators. With a mindset rooted in openness, value creation, and adaptability, we navigate the innovation ecosystem to drive transformative impact and future readiness across the organization.

The IA Principal Data Scientist plays a pivotal role in building and deploying AI/ML‑powered digital solutions that transform how we develop medicines. You will 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. With a strong product‑thinking mindset and deep technical fluency, you will help create intelligent tools that are scalable, ethical, and built for impact in regulated healthcare environments.

Responsibilities

• Support or lead the development and application of advanced statistical and machine learning methods for integration into tools and software products in clinical development and decision‑making support.
• Design and productize the execution of simulation studies to evaluate innovative trial designs and statistical frameworks.
• Translate complex scientific and operational considerations into software requirements that productize model development and usage, collaborating with domain experts to validate assumptions and interpret results.
• Independently drive exploratory analysis of complex clinical, biomarker, and operational data to extract insights and develop predictive models.
• Develop scalable, reproducible pipelines for data processing, model training, evaluation, and deployment in regulated environments.
• Optimize model performance, ensure algorithmic fairness, proactively mitigate bias or drift in deployed systems, and develop evaluation approaches for algorithms including generative AI (GenAI) components.
• Co‑lead the architectural design of ML and GenAI systems supporting traceability, compliance, and explainability.
• Partner with software engineering, product, UX, and science teams to integrate models into real‑world user applications.
• Contribute to scientific leadership by publishing and presenting novel methodologies in high‑impact venues, both internal and external.
• Serve as a best‑practice resource for statistical modeling strategies, code quality, and responsible AI principles.
• Lead or co‑lead cross‑functional data science efforts that impact portfolio strategy and delivery.

Qualifications

• Master’s or PhD in Data Science, Computer Science, Statistics, Applied Mathematics, Bioinformatics, or a related field.
• 6+ years of experience applying advanced statistical and ML techniques in biomedical, clinical, or digital health domains.
• Proven expertise in model development, simulation studies, and decision‑support frameworks.
• Strong hands‑on experience with Python or R, and ML libraries such as scikit‑learn, TensorFlow, PyTorch, or similar.
• Track record of translating complex domain questions into robust statistical models or ML systems.
• Experience building pipelines for training, evaluating, and deploying ML solutions in production environments.
• Demonstrated expertise with real‑world data, Bayesian methods, decision theory, high‑dimensional data, or causal inference.
• Attention to detail and quality work with ability to manage and prioritize multiple projects simultaneously.
• Excellent collaboration skills, including statistical consulting skills, interpersonal skills to contribute effectively in cross‑functional team settings, ability to influence others without authority.
• Capacity for independent thinking and ability to make decisions based upon sound principles.
• Excellent strategic agility with problem‑solving and critical thinking skills.
• Respect for cultural differences when interacting with colleagues in the global workplace.
• Excellent verbal and written communication skills, specifically in the areas of presentation and writing, with ability to explain complex technical concepts in clear language.

Preferred Qualifications

• Experience leading technical design or mentoring junior team members.
• Experience applying Agile software development practices, ideally for a product embedding statistical algorithms and/or GenAI.
• Experience prototyping and launching innovative data science or AI products.
• Experience deploying ML models in compliant, regulated environments.
• Experience developing evidence synthesis models or methods (e.g., network meta‑analysis) and/or approaches to construct data‑driven priors for drug development.
• Experience with Bayesian computing or probabilistic programming languages (PPLs), including Stan, PyMC, brms, or others.
• Experience with AI‑native software engineering practices.
• Familiarity with data governance, privacy, and regulatory frameworks relevant to ML in pharma.
• Exposure to multiple stages of the pharma development life‑cycle (e.g., early development, assessment of external molecules for business development, commercialization).
• Familiarity with cloud‑native ML architectures, ML Ops tools, or real‑world data pipelines.
• Strong publication record or external visibility in scientific communities.

Location

Boston, MA. Relocation assistance is not available.

Compensation

The expected salary range for this position based on the primary location of Boston, Massachusetts is $169,100 - $314,000 USD annual. 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.

Benefits 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.