Expert Data Scientist, Early Clinical Development
Genentech · South San Francisco, CA
- On site
- Full-time
- $250,000 / year
- South San Francisco, CA
Job highlights
- Lead data review capabilities with AI/ML.
- Develop advanced visualizations and analytical applications.
- Collaborate with clinical and technical teams.
- Automate data mapping, transformation, and review.
- Drive adoption of new data technologies.
About the role
Expert Data Scientist, Early Clinical Development
Genentech is advancing science to give people more time with loved ones.
About the Role
As an Expert Data Scientist in Early Clinical Development (ECD), you will be a key player in leveraging data visualization, data analysis, data insights, and applied AI/ML-enabled analytics. You will empower stakeholders to efficiently review and analyze data from internal studies and external published sources. You will collaborate closely with ECD clinical disease area leads, Safety Scientists, and other functional colleagues to thoroughly explore scientific questions related to specific indications or diseases. This involves employing creative data analysis, analytical applications, data visualizations, automation, and innovative approaches.
Your primary responsibility will be to provide strategic and technical direction for the development, implementation, and ongoing enhancement of Early Clinical Development data review capabilities at the indication, program, and study levels. You will focus on developing scalable solutions and processes that generate significant organizational impact, while actively seeking opportunities to simplify, automate, innovate, and collaborate with experts both within and outside of ECD.
Furthermore, you will manage the implementation and adoption of medical data review and visualization applications by offering training, consultation, and dedicated support. This role contributes to the ECD portfolio-level review and visualization capabilities and helps to evolve current workflows through automation, data-driven processes, and the practical application of AI and advanced technologies where suitable.
The Opportunity
- Strategically utilize internal and external data to develop advanced data visualizations and analytical applications tailored for gRED Early Clinical Development. Identify opportunities to apply AI, automation, and scalable digital solutions to enhance medical data review efficiency.
- Serve as the primary point of contact for Therapeutic Area or disease area leads, addressing questions on specific disease-area data exploratory analysis and medical data review needs. Explore opportunities to modernize review workflows through automation, chatbot-enabled access, or AI-assisted data exploration.
- Provide guidance, training, consultation, and dedicated support for medical data review and analytical visualization tools. Focus on the adoption of modern technologies, automation-enabled workflows, and AI/ML-supported analytical capabilities.
- Collaborate within ECD and with other line functions, including AI engineers, software engineers, and platform teams. Align and simplify processes, prevent redundancy in analytics, and accelerate data-driven decision-making through automation, reusable solutions, and scalable data-driven processes.
- Co-lead AI/automation-focused projects with technical partners by translating business needs into technical requirements, supporting solution design, and ensuring outputs are practical, scalable, and aligned with clinical stakeholder needs.
- Create derived datasets from raw clinical trial data to support medical data review, statistical analysis, visualization, and reporting. Contribute to the automation of data mapping, transformation, standardization, and quality review processes where feasible.
- Write detailed specifications for datasets, tables, analyses, visualizations, analytical applications, and automation-enabled workflows based on clinical, business, and regulatory requirements. Collaborate with AI/software engineering partners for effective implementation.
- Develop and maintain standard programming packages, reusable functions, automation components, AI/ML-enabled utilities, and tools to improve efficiency and ensure compliance with industry standards.
- Utilize strong technical expertise and skills to identify opportunities for innovation, efficiency, simplification, automation, and the practical application of AI or advanced technologies with a focus on working smarter.
- Collaborate across teams to bridge business needs with technical implementation, drive adoption of modern technologies and scalable solutions, and help shape future ways of working for medical data review and analytical applications.
Who You Are:
- 5+ years of experience with a Bachelor’s degree; 3+ years with a Master’s degree; 1+ years with a PhD in statistics, computer science, data science, biomedical informatics, engineering, mathematics, or a relevant technical discipline.
- Significant experience in clinical trial data analysis, medical data review, data visualization, or analytical application development within the pharmaceutical or biotech industry.
- Strong understanding of the data flow in the end-to-end drug development lifecycle, with the ability to translate clinical data review needs into technical requirements for analytics, automation, and AI-enabled solutions.
- Experience creating SDTM, ADaM, derived datasets, and/or developing TFLs using SAS, R, Python, or related tools. Interest or experience in automating data mapping, transformation, quality review, and analytical workflows.
- Experience with clinical data visualization tools such as Spotfire, Tableau, R/Shiny, or similar analytical applications, including implementation, user support, and continuous improvement of tools used by clinical stakeholders.
- Experience applying, supporting, or co-leading automation, advanced analytics, AI/ML, NLP, LLMs, chatbots, or agentic workflow solutions to practical business problems is preferred.
- Ability to work closely with AI engineers, platform teams, and clinical stakeholders to co-lead AI/automation projects from business problem definition through technical implementation, user adoption, and continuous improvement.
- Experience translating business needs into technical requirements, scalable analytical solutions, automation workflows, and implementation plans in partnership with technical teams.
- Demonstrated ability to provide training, consultation, implementation support, and dedicated user support for analytical tools, medical data review applications, or AI/automation-enabled workflows.
- Experience driving adoption of modern technologies, automation, analytics, or scalable digital solutions across teams, including helping stakeholders understand and use new capabilities effectively.
- Track record of establishing successful partnerships across organizations.
- Excellent written and verbal communication skills, strong project management skills, and the ability to navigate in a complex, international, and matrixed environment.
Key skills/competency
- Expert Data Scientist
- Data Visualization
- Data Analysis
- Applied AI/ML
- Clinical Trial Data
- Pharmaceutical Industry
- SAS
- R
- Python
- Tableau
Skills & topics
- Data Scientist
- Data Visualization
- Data Analysis
- AI
- Machine Learning
- Clinical Trials
- Pharmaceutical
- Biotech
- SAS
- Python
- R
- Tableau
- Spotfire
- Early Clinical Development
How to get hired
- Tailor your resume: Highlight experience with clinical trial data, data visualization, and AI/ML applications relevant to early clinical development. Quantify achievements where possible.
- Showcase technical skills: Emphasize proficiency in SAS, R, Python, and data visualization tools like Spotfire or Tableau. Mention experience with SDTM, ADaM, and derived datasets.
- Demonstrate collaboration: Provide examples of working with clinical stakeholders, AI engineers, and platform teams to translate business needs into technical solutions.
- Prepare for technical and behavioral interviews: Be ready to discuss your experience with AI/ML projects, automation workflows, and how you handle complex, matrixed environments.
- Research Genentech: Understand their mission in advancing science and improving patient lives, and how this role contributes to that mission.
Technical preparation
Master clinical trial data structures (SDTM, ADaM).,Practice Python, R, or SAS for data manipulation.,Build interactive visualizations with Tableau or Shiny.,Develop AI/ML models for data analysis.
Behavioral questions
Describe a complex data problem you solved.,How do you translate business needs to tech specs?,Share an experience driving technology adoption.,How do you collaborate with diverse teams?
Frequently asked questions
- What are the key technical skills required for the Expert Data Scientist role at Genentech?
- The Expert Data Scientist role at Genentech requires significant experience in clinical trial data analysis, medical data review, data visualization, and analytical application development. Proficiency in programming languages such as SAS, R, or Python is essential, along with experience in creating datasets like SDTM and ADaM, and developing TFLs. Familiarity with clinical data visualization tools like Spotfire, Tableau, or R/Shiny is also crucial. Experience with automation, advanced analytics, AI/ML, NLP, LLMs, chatbots, or agentic workflows is preferred.
- How does Genentech foster innovation and the adoption of new technologies in Early Clinical Development?
- Genentech encourages innovation by empowering the Expert Data Scientist to identify opportunities for simplification, automation, and the practical application of AI and advanced technologies. This includes co-leading AI/automation projects, translating business needs into technical requirements, and ensuring practical, scalable solutions. The role also involves driving the adoption of modern technologies and scalable digital solutions across teams, providing training and support to help stakeholders effectively use new capabilities.
- What is the expected onsite presence for the Expert Data Scientist at Genentech's South San Francisco campus?
- The Expert Data Scientist position requires an onsite presence at Genentech's South San Francisco campus for at least 3 days a week. This hybrid work arrangement allows for in-person collaboration while offering some flexibility.
- What is the salary range for the Expert Data Scientist position in South San Francisco?
- The expected salary range for the Expert Data Scientist position in South San Francisco is $185,200 to $343,900 annually. The final salary will be determined based on factors such as experience, qualifications, geographic location, and other job-related criteria. Additionally, a discretionary annual bonus and comprehensive benefits are available.
- What kind of collaboration can I expect as an Expert Data Scientist at Genentech?
- As an Expert Data Scientist at Genentech, you will collaborate extensively within ECD and with other line functions, including AI engineers, software engineers, and platform teams. You will also work closely with clinical disease area leads and Safety Scientists. This collaborative environment is key to aligning processes, preventing redundancy, and accelerating data-driven decision-making through automation and scalable solutions.
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