Job description

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 Senior 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 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 You act as the subject matter expert to inform software products for the conduct of simulation studies and comparative evaluations of analytical approaches for clinical and operational scenarios You collaborate with domain experts to translate scientific problems into data science workflows, identifying patterns of workflows that can be automated and productized You build and maintain model development pipelines, ensuring traceability, performance monitoring, and reproducibility You contribute to the integration of models and algorithms into production applications, working closely with engineering and product teams You participate in the design of compliant and interpretable ML product architectures for clinical development environments You design documentation templates that communicate modeling decisions, trade-offs, and performance summaries to cross-functional stakeholders You contribute to internal knowledge sharing, peer reviews, and community learning within the data science function 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 3 years of experience applying machine learning and statistical modeling to data-centric problems in research or product environments You are proficient with Python or R, including experience with ML libraries such as scikit-learn, XGBoost, TensorFlow, or PyTorch You have experience in experimental design, simulation, and evaluation of model performance You have the ability to translate scientific or business questions into model architectures and data pipelines You have practical experience with version control, testing frameworks, and collaborative software development You have experience working with one or more of the following: RWD/RWE, decision analysis, clinical biomarkers, Bayesian inference, or interpretable ML 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 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 (PPLs), including Stan, PyMC, brms, or others Experience with collaborative coding practices and modern version control (e.g., git, CI/CD) Experience with generative AI tooling for software development (e.g., agentic coding, spec-driven development, AI code reviews) Experience developing agentic AI tooling for data analysis or processes 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 The expected salary range for this position based on the primary location of Boston, Massachusetts is $142,700 - $264,900 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. 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 .

Requirements

Must-haves

You 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
You act as the subject matter expert to inform software products for the conduct of simulation studies and comparative evaluations of analytical approaches for clinical and operational scenarios
You collaborate with domain experts to translate scientific problems into data science workflows, identifying patterns of workflows that can be automated and productized
You build and maintain model development pipelines, ensuring traceability, performance monitoring, and reproducibility
You contribute to the integration of models and algorithms into production applications, working closely with engineering and product teams
You participate in the design of compliant and interpretable ML product architectures for clinical development environments
You design documentation templates that communicate modeling decisions, trade-offs, and performance summaries to cross-functional stakeholders
You contribute to internal knowledge sharing, peer reviews, and community learning within the data science function
You have a Master’s or PhD in Data Science, Computer Science, Statistics, Applied Mathematics, Bioinformatics, or a related field
You have 3 years of experience applying machine learning and statistical modeling to data-centric problems in research or product environments
You are proficient with Python or R, including experience with ML libraries such as scikit-learn, XGBoost, TensorFlow, or PyTorch
You have experience in experimental design, simulation, and evaluation of model performance
You have the ability to translate scientific or business questions into model architectures and data pipelines
You have practical experience with version control, testing frameworks, and collaborative software development

Nice-to-haves

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 (PPLs), including Stan, PyMC, brms, or others
Experience with collaborative coding practices and modern version control (e.g., git, CI/CD)
Experience with generative AI tooling for software development (e.g., agentic coding, spec-driven development, AI code reviews)
Experience developing agentic AI tooling for data analysis or processes 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
Relocation Assistance is not available

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

aimlmachine learningpythonci/cdagile

Platform: workday
Effort: long

Benefits

Benefits detected in the listing.

Vision