Senior Data Scientist (AI-assisted Clinical Development)

Posted Yesterday
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Boston, MA, USA
In-Office
143K-265K Annually
Senior level
Healthtech • Biotech
The Role
Design, develop, and deploy ML and statistical solutions for clinical development. Partner with product, engineering, and domain experts to build reproducible model pipelines, run simulation and comparative evaluations, integrate models into production, and ensure compliant, interpretable ML architectures. Produce documentation, monitor performance, and contribute to knowledge sharing and cross-functional productization of data science solutions in regulated healthcare environments.
Summary Generated by Built In

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.

Skills Required

  • Master's or PhD in Data Science, Computer Science, Statistics, Applied Mathematics, Bioinformatics, or related field
  • 3+ years applying machine learning and statistical modeling in research or product environments
  • Proficiency with Python or R
  • Experience with ML libraries such as scikit-learn, XGBoost, TensorFlow, or PyTorch
  • Experience in experimental design, simulation, and model performance evaluation
  • 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 with one or more: RWD/RWE, decision analysis, clinical biomarkers, Bayesian inference, or interpretable ML
  • Attention to detail and ability to manage and prioritize multiple projects
  • Strong collaboration and statistical consulting skills for cross-functional teams
  • Independent thinking and decision-making capacity
  • Strategic agility, problem-solving, and critical thinking skills
  • Respect for cultural differences in a global workplace
  • Excellent verbal and written communication, presentation and writing skills

Genentech Compensation & Benefits Highlights

The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Genentech and has not been reviewed or approved by Genentech.

  • Healthcare Strength Health coverage is described as comprehensive across medical, dental, vision, mental health, and prescriptions, supported by HSAs/FSAs and broad wellness resources. On‑site fitness and health centers, mental‑health clinicians, and specialized programs like fully covered preventive cancer screenings and menopause support deepen the offering.
  • Retirement Support Retirement benefits feature a 401(k) with up to a 4% company match plus an additional annual 6% company contribution to eligible pay. Additional financial protections such as life and accident insurance complement salary, bonuses, and stock options.
  • Leave & Time Off Breadth Time away includes about 20 paid vacation days, paid holidays, personal days, and a year‑end shutdown. A paid six‑week sabbatical every six years notably expands long‑term time‑off flexibility.

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The Company
HQ: South San Francisco, CA
20,069 Employees
Year Founded: 1976

What We Do

Considered the founder of the industry, Genentech, now a member of the Roche Group, has been delivering on the promise of biotechnology for more than 40 years. Genentech is a biotechnology company dedicated to pursuing groundbreaking science to discover and develop medicines for people with serious and life-threatening diseases. Our transformational discoveries include the first targeted antibody for cancer and the first medicine for primary progressive multiple sclerosis. We're passionate about finding solutions for people facing the world's most difficult-to-treat conditions. That is why we use cutting-edge science to create and deliver innovative medicines around the globe. To us, science is personal. Making a difference in the lives of millions starts when you make a change in yours.

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