1.54M jobs liveBrowse

Senior Data Scientist (AI-assisted Clinical Development) at Genentech, Inc. · Katori

Asks for

The ad says“You have experience working with one or more of the following: RWD/RWE, decision analysis, clinical biomarkers, Bayesian inference, or interpretable ML”
The ad says“You have experience working with one or more of the following: RWD/RWE, decision analysis, clinical biomarkers, Bayesian inference, or interpretable ML”
The ad says“You have experience working with one or more of the following: RWD/RWE, decision analysis, clinical biomarkers, Bayesian inference, or interpretable ML”
The ad says“You have experience in experimental design, simulation, and evaluation of model performance”
The ad says“You have experience in experimental design, simulation, and evaluation of model performance”
The ad says“You have experience working with one or more of the following: RWD/RWE, decision analysis, clinical biomarkers, Bayesian inference, or interpretable ML”
The ad says“You are proficient with Python or R, including experience with ML libraries such as scikit-learn, XGBoost, TensorFlow, or PyTorch”
The ad says“You are proficient with Python or R, including experience with ML libraries such as scikit-learn, XGBoost, TensorFlow, or PyTorch”
The ad says“You are proficient with Python or R, including experience with ML libraries such as scikit-learn, XGBoost, TensorFlow, or PyTorch”
The ad says“You have experience working with one or more of the following: RWD/RWE, decision analysis, clinical biomarkers, Bayesian inference, or interpretable ML”
The ad says“You are proficient with Python or R, including experience with ML libraries such as scikit-learn, XGBoost, TensorFlow, or PyTorch”
The ad says“You have experience in experimental design, simulation, and evaluation of model performance”
The ad says“You have practical experience with version control, testing frameworks, and collaborative software development”
The ad says“You are proficient with Python or R, including experience with ML libraries such as scikit-learn, XGBoost, TensorFlow, or PyTorch”
The ad says“You have practical experience with version control, testing frameworks, and collaborative software development”
The ad says“You have practical experience with version control, testing frameworks, and collaborative software development”
The ad says“You are proficient with Python or R, including experience with ML libraries such as scikit-learn, XGBoost, TensorFlow, or PyTorch”

Values

The ad says“Experience developing agentic AI tooling for data analysis or processes relevant to the pharmaceutical industry”
The ad says“Experience with generative AI tooling for software development (e.g., agentic coding, spec-driven development, AI code reviews)”
The ad says“Experience with generative AI tooling for software development (e.g., agentic coding, spec-driven development, AI code reviews)”
The ad says“Experience with Bayesian computing or probabilistic programming languages (PPLs), including Stan, PyMC, brms, or others”
The ad says“Experience with Bayesian computing or probabilistic programming languages (PPLs), including Stan, PyMC, brms, or others”
The ad says“Experience with collaborative coding practices and modern version control (e.g., git, CI/CD)”
The ad says“Experience contributing to ML product pipelines and deployment workflows”
The ad says“Experience building evidence synthesis models (e.g., network meta-analysis) or constructing data-driven priors for drug development”
The ad says“Experience with generative AI tooling for software development (e.g., agentic coding, spec-driven development, AI code reviews)”
The ad says“Experience with collaborative coding practices and modern version control (e.g., git, CI/CD)”
The ad says“Knowledge of compliance-related standards (e.g., GxP, HIPAA)”
The ad says“Knowledge of compliance-related standards (e.g., GxP, HIPAA)”
The ad says“Experience contributing to ML product pipelines and deployment workflows”
The ad says“Experience building evidence synthesis models (e.g., network meta-analysis) or constructing data-driven priors for drug development”
The ad says“Experience with Bayesian computing or probabilistic programming languages (PPLs), including Stan, PyMC, brms, or others”
The ad says“Experience with Bayesian computing or probabilistic programming languages (PPLs), including Stan, PyMC, brms, or others”
The ad says“Experience with generative AI tooling for software development (e.g., agentic coding, spec-driven development, AI code reviews)”
The ad says“Experience with Bayesian computing or probabilistic programming languages (PPLs), including Stan, PyMC, brms, or others”

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.