Senior Principal DSX Data Scientist, AI

Genentech

Confirmed live yesterday High trust

Quick summary

Work type
On-site
Location
South San Francisco, CA
Salary
$207,480–$385,320 / yr
Posted
23 days ago
Freshness
Confirmed live yesterday

Market check

Salary context

Above market

How this pay compares to similar roles

Similar $182k
This role $296k
$105k most similar roles pay here $415k

This role pays more than 99% of similar roles. Most pay $155,100–$208,822 — the shaded band above. At the midpoint, this role pays about $296k versus about $182k for comparable roles.

Based on 239 similar postings.

Employer

About Genentech

Genentech is a leading research-driven company dedicated to discovering and developing, manufacturing, and commercializing medicines for people with serious and life-threatening diseases.

Genentech currently has 10 open roles on FindRole.

Listed pay typically runs $150,200–$279,000 across 9 roles with salary data.

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View all roles at Genentech

At a glance

TL;DR · Senior Principal DSX Data Scientist, AI

The Senior Principal DSX Data Scientist joins the Data Science Acceleration team within Product Development Data Sciences to provide strategic leadership in developing scalable tools, environments, and workflows for statistical computing. This role involves building next-generation capabilities to automate programming workflows, create reusable coding macros, and develop advanced data visualizations. The successful candidate will translate scientific needs into robust, modular solutions while serving as a senior technical advisor on infrastructure and automation. Key responsibilities include leading large-scale cross-functional initiatives, defining architectural decisions, and influencing internal development standards. The role requires expertise in Python and R to support reproducible, compliant, and high-performance computing. This position addresses the challenge of streamlining evidence generation and accelerating decision-making across the clinical development pipeline by integrating complex data processing with advanced scientific computing systems within a regulated research environment.

What you'll do

  • Develop scalable tools, environments, and workflows to enable efficient statistical computing across the product development pipeline.
  • Create and maintain next-generation capabilities for automating programming workflows and generating reusable coding macros.
  • Design advanced data visualization solutions to streamline evidence generation and support faster decision-making.
  • Provide technical leadership on the design and evolution of the organization's statistical computing platforms.
  • Translate emerging industry trends and regulatory shifts into forward-looking data science capabilities and standards.
  • Lead large-scale, cross-functional initiatives to improve how clinical, operational, and real-world data are processed.
  • Serve as a senior technical advisor on complex infrastructure, automation, and scientific computing topics.
  • Influence internal policies and development standards to drive the adoption of best practices across global teams.

What we're looking for

  • Hold a PhD or Master’s degree in Computer Science, Data Science, Statistics, Bioinformatics, Engineering, or a related quantitative field.
  • Minimum of 8 years of experience in data science, statistical computing, or platform development with a track record of organizational impact.
  • Expert knowledge in building and scaling scientific or statistical software systems within clinical research environments and regulatory frameworks.
  • Proficiency in multiple programming environments, such as Python and R, for reproducible and high-performance computing.
  • Proven experience leading large-scale, cross-functional projects and technical initiatives with strategic significance.
  • Excellent verbal and written communication skills to influence senior stakeholders and explain complex technical strategies.
  • Experience shaping the architecture and long-term roadmap of enterprise-scale data science platforms (preferred).
  • Demonstrated ability to influence regulatory and quality frameworks regarding digital and analytical tools (preferred).

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