Principal Data Scientist (AI-assisted Clinical Development)

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 Opportunity: 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. You 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

You design and productize the execution of simulation studies to evaluate innovative trial designs and statistical frameworks

You translate complex scientific and operational considerations into software requirements that productize model development and usage, collaborating with domain experts to productize the validation of assumptions and result interpretation

You independently drive exploratory analysis of complex clinical, biomarker, and operational data to extract insights and develop predictive models

You develop scalable, reproducible pipelines for data processing, model training, evaluation, and deployment in regulated environments

You 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

You co-lead the architectural design of ML and GenAI systems supporting traceability, compliance, and explainability

You partner with software engineering, product, UX, and science teams to integrate models into real-world user applications

You contribute to scientific leadership by publishing and presenting novel methodologies in high-impact venues, both internal and external

You serve as a best-practice resource for statistical modeling strategies, code quality, and responsible AI principles

You lead or co-lead cross-functional data science efforts that impact portfolio strategy and delivery

Who you are

You have a Master’s or PhD in Data Science, Computer Science, Statistics, Applied Mathematics, Bioinformatics, or a related field

You have 6+ years of experience applying advanced statistical and ML techniques in biomedical, clinical, or digital health domains

You have proven expertise in model development, simulation studies, and decision-support frameworks

You have strong hands-on experience with Python or R, and ML libraries such as scikit-learn, TensorFlow, PyTorch, or similar

You have a track record of translating complex domain questions into robust statistical models or ML systems

You have experience building pipelines for training, evaluating, and deploying ML solutions in production environments

You have demonstrated expertise with RWD, Bayesian methods, decision theory, high-dimensional data, or causal inference

You have attention to detail and quality work with an ability to manage and prioritize multiple projects simultaneously, including both long-term and short-term initiatives

You have excellent collaboration skills, including statistical consulting skills, interpersonal skills to contribute effectively in cross-functional team settings, ability to influence others without authority, and ability to build strong collaborative relationships with scientific and non-scientific partners

You have capacity for independent thinking and ability to make decisions based upon sound principles

You exhibit excellent strategic agility including problem-solving and critical thinking skills, and agility that extends beyond technical domain

You demonstrate respect for cultural differences when interacting with colleagues in the global workplace

You possess excellent verbal and written communication skills, specifically in the areas of presentation and writing, with the ability to explain complex technical concepts in clear language

Preferred: 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 This position is based in Boston, MA

Relocation assistance is not available

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. This position also qualifies for the benefits detailed at the link provided below. Benefits

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.

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