Expert Data Scientist, Early Clinical Development

GenentechDaly City, CA
$185,200 - $343,900Hybrid

About The Position

We advance science so that we all have more time with the people we love. The Expert Data Scientist is an expert in data visualization, data analysis, data insights, and applied AI/ML-enabled analytics, enabling stakeholders to efficiently and effectively review and analyze data from internal studies and external published data. The Expert Data Scientist works directly with ECD clinical disease area leads, Safety Scientists, and other line function colleagues to ensure that indication- or disease-specific scientific questions are explored thoroughly using creative data analysis, analytical applications, data visualizations, automation, and fit-for-purpose innovation. Your primary responsibility will be to provide strategic and technical direction for the development, implementation, and continuous improvement of Early Clinical Development data review capabilities at the indication, program, and study level. You will develop scalable solutions and processes that create organizational impact, while continuously identifying opportunities to simplify, automate, innovate, and collaborate with experts within and outside of ECD. The Expert Data Scientist also manages implementation and adoption of medical data review and visualization applications by providing training, consultation, and dedicated support. The role contributes to ECD portfolio-level review and visualization capabilities, while helping evolve current workflows through automation, data-driven processes, and practical application of AI and advanced technologies where appropriate.

Requirements

  • 5+ years of experience with Bachelor’s; 3+ years with Master’s; 1+ years with 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 in 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, with 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.
  • 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.

Nice To Haves

  • Experience applying, supporting, or co-leading automation, advanced analytics, AI/ML, NLP, LLMs, chatbots, or agentic workflow solutions to practical business problems is preferred.

Responsibilities

  • Strategically uses internal and external data to develop advanced data visualizations and analytical applications that are fit-for-purpose for gRED Early Clinical Development, while identifying opportunities to apply AI, automation, and scalable digital solutions to improve medical data review efficiency.
  • Acts as a main point of contact for Therapeutic Area leads or disease area leads with questions on specific disease-area data exploratory analysis and medical data review needs, including opportunities to modernize review workflows through automation, chatbot-enabled access, or AI-assisted data exploration where appropriate.
  • Provides guidance, training, consultation, and dedicated support for medical data review and analytical visualization tools, including adoption of modern technologies, automation-enabled workflows, and AI/ML-supported analytical capabilities.
  • Collaborates within ECD and other line functions, including AI engineers, software engineers, and platform teams, to align and simplify processes, prevent redundancy in analytics, and accelerate data-driven decision-making through automation, reusable solutions, and scalable data-driven processes.
  • Co-leads 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.
  • Creates derived datasets from raw clinical trial data to support medical data review, statistical analysis, visualization, and reporting, and contributes to automation of data mapping, transformation, standardization, and quality review processes where feasible.
  • Writes detailed specifications for datasets, tables, analyses, visualizations, analytical applications, and automation-enabled workflows based on clinical, business, and regulatory requirements, and collaborates with AI/software engineering partners to ensure effective implementation.
  • Develops and maintains standard programming packages, reusable functions, automation components, AI/ML-enabled utilities, and tools to improve efficiency and ensure compliance with industry standards.
  • Uses strong technical expertise and skills to find opportunities for innovation, efficiency, simplification, automation, and practical application of AI or advanced technologies with the mindset of working smarter.
  • Collaborates 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.

Benefits

  • Relocation benefits are not available for this posting.
  • 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.
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