Senior Data Scientist (AI-assisted Clinical Development)
About The Position
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 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.
Requirements
- 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 the following: RWD/RWE, decision analysis, clinical biomarkers, Bayesian inference, or interpretable ML
- Attention to detail and quality work with an ability to manage and prioritize multiple projects simultaneously, including both long-term and short-term initiatives
- 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
- Capacity for independent thinking and ability to make decisions based upon sound principles
- Excellent strategic agility including problem-solving and critical thinking skills, and agility that extends beyond technical domain
- 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 the ability to explain complex technical concepts in clear language
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
Responsibilities
- 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 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
- 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
Benefits
- Discretionary annual bonus may be available based on individual and Company performance.
- Benefits detailed at the link provided below.
Stand Out From the Crowd
Upload your resume and get instant feedback on how well it matches this job.
What This Job Offers
Job Type
Full-time
Career Level
Senior
