Genentech

Senior Director, Data Science Solutions

Genentech$255K — $475K *
Pharmaceuticals & Biotech
8 - 10 years of experience
Job Overview by Ladders

Qualifications

  • Master's degree in a quantitative field; PhD preferred.
  • 10+ years in data science, AI/ML in biopharma.
  • Deep healthcare data understanding.
  • Proven success in enterprise operational modernization.
  • Experience with vendor partnerships and technology solution implementations.
  • Strong AI/ML integration knowledge across enterprises.
  • Excellent leadership and communication skills.

Responsibilities

  • Lead strategy execution for biopharma data science solutions.
  • Develop solution roadmaps aligned with enterprise needs.
  • Drive adoption of data science solutions in workflows.
  • Manage partnerships with external vendors for AI/ML solutions.
  • Oversee implementation of data science capabilities.
  • Establish scalable operational models for deployment.
  • Collaborate across departments for effective data solution integration.

Benefits

  • Relocation assistance available.
  • Access to a diverse and high-performing team.
  • Opportunities for career development and training.
  • Performance management and rewards system.
  • Involvement in cutting-edge biopharma technology projects.
Full Job Description
Job Summary

The Senior Director, Data Science Solutions will lead the strategy, prioritization, and deployment of industry-validated biopharma data science solutions that accelerate modernization of Genentech's Commercial Engine and enterprise decision capabilities.

This role will serve as a senior leader within the DSML organization, responsible for identifying, adopting, and operationalizing specialized biopharma data science capabilities that improve the speed and effectiveness of commercial and business operations.

Through strategic external partnerships, this leader and team will establish and leverage industry-validated data science solutions to:
  • rapidly deliver ad hoc data science-powered advanced analytical capabilities and business insights,
  • accelerate adoption and operational integration of enterprise AI products and data science solutions,
  • and enable business organizations to effectively utilize modern DS/AI-enabled decision capabilities at scale.

The position will focus on accelerating adoption of industry-validated solutions through strategic vendor partnerships, solution prioritization, roadmap development, implementation leadership, and cross-functional operational integration. This leader will ensure deployed solutions are practical, scalable, interoperable, and aligned with Genentech's evolving business priorities and enterprise AI ecosystem.

In the near term, this role will provide technical and strategic leadership for vendor-delivered data science solutions supporting commercial and operational modernization initiatives. Over time, the role will establish scalable implementation models, reusable operational patterns, and sustainable enterprise capabilities that accelerate adoption of modern DS/AI-enabled business operations across Genentech.

This leader will collaborate extensively across DSML, Insight & Analytics (I&A), Data Product Management (DPM), Digital Experiences (DE), Roche Digital & Technology (RDT), and external strategic partners to drive practical and scalable deployment of data science capabilities across the enterprise.

Key Job Responsibilities
Strategic Leadership & Commercial Engine Modernization
  • Define and execute the strategy for industry-validated data science solutions that modernize Genentech's Commercial Engine and deliver scalable business value.
  • Develop solution roadmaps aligned to enterprise priorities, operational needs, vendor capabilities, and technology strategy.
  • Drive scalable adoption of industry-validated data science solutions across commercial and operational workflows.
  • Establish scalable approaches to rapidly deliver ad hoc data science-powered advanced analytical capabilities and decision support solutions to business partners.
  • Evaluate external partnership opportunities to accelerate enterprise modernization with industry-validated data science solutions.
  • Partner with senior business and technology leaders to align solution priorities with enterprise strategic objectives.

Vendor Partnership & Solution Delivery
  • Lead strategic partnerships with external vendors and solution providers delivering industry-validated AI/ML and data science solutions.
  • Evaluate vendor solutions for scalability, operational fit, technical quality, implementation readiness, and enterprise compatibility.
  • Provide implementation leadership and technical oversight for externally delivered solutions.
  • Partner with procurement, legal, security, and business stakeholders to support effective vendor engagement and delivery execution.
  • Ensure external solutions align with enterprise technology, security, and operational standards.

Implementation & Operational Scaling
  • Lead deployment and operationalization of industry-validated data science solutions across CMG environments.
  • Utilize, and drive cross-organizational adoption of, implemented data science solutions.
  • Establish repeatable implementation patterns and scalable operational models for enterprise capability deployment.
  • Partner with business and technology stakeholders to accelerate modernization of operational workflows and decision enablement capabilities.
  • Support scalable deployment aligned with enterprise operational and technology requirements.

Cross-Functional Leadership
  • Partner closely with DSML teams, Insight & Analytics (I&A), Data Product Management (DPM), Digital Experiences (DE), and Roche Digital & Technology (RDT) organizations to align data science solutions with enterprise priorities and technology ecosystems.
  • Serve as a strategic advisor across technical and business organizations to drive adoption of established data science solutions.
  • Influence senior stakeholders and drive alignment across highly matrixed organizations.


People
  • Attract, lead, and develop highly-connected, highly-motivated and high-performing teams.
  • Provide guidance, training, and career development opportunities for team members.
  • Drive a culture of employee engagement and accountability through performance management, incentive alignment, and rewards and recognition of all team members.


Minimum Qualifications & Experience
  • Master's degree in Data Science, Statistics, Computer Science, Engineering, Biostatistics, or related quantitative field required; PhD preferred.
  • 10+ years of experience in data science, AI/ML, advanced computational solutions, or related technical disciplines within biotechnology and/or pharmaceutical industries.
  • Deep understanding of healthcare data and data-informed decision processes.
  • Proven record in driving successful enterprise operational modernization and deployment of scalable data science and AI/ML capabilities.
  • Demonstrated experience leading external vendor partnerships, consulting engagements, or third-party technology solution implementations.
  • Experience leading enterprise-scale implementation and operationalization of AI/ML and data science capabilities within complex organizations.
  • Strong understanding of scalable AI/ML technologies, operational deployment models, and enterprise solution integration approaches.
  • Experience working cross-functionally across business, technology, and operational organizations.
  • Proven leadership experience in matrixed organizations with multiple senior stakeholders.
  • Excellent communication, stakeholder management, prioritization, and executive influence capabilities.
  • Strong leadership and team management abilities, with experience coaching and developing high-performing teams.


Preferred Qualifications & Experience
  • PhD in Data Science, Statistics, Computer Science, Engineering, Biostatistics, or related field preferred.
  • Experience with industry-validated biopharma data science solution ecosystems and commercial AI/ML enablement platforms.
  • Familiarity with modern AI/ML platforms, cloud technologies, enterprise operational deployment frameworks, and scalable enterprise architectures.
  • Experience leading vendor-delivered data science solution implementation roadmaps and enterprise modernization initiatives.
  • Demonstrated success accelerating organizational adoption of scalable enterprise AI and data science capabilities.
  • Experience balancing strategic innovation with operational execution and enterprise business enablement.
  • Experience working within highly matrixed organizations across multiple therapeutic areas or enterprise functions.


Location
  • This position is based in South San Francisco, CA.
  • Relocation assistance is available.


The expected salary range for this position based on the primary location of South San Francisco, CA is $255,900 - $475,200 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

*LI-NN2

About Genentech

Genentech is a biotechnology company that develops and manufactures drugs for the treatment of serious medical conditions. The company was founded in 1976 and is headquartered in South San Francisco, California. Genentech's products include treatments for cancer, multiple sclerosis, and other diseases. The company is a subsidiary of Roche, a Swiss pharmaceutical company. Genentech has been recognized for its innovative research and development, and has received numerous awards for its contributions to the biotechnology industry.
Learn more about Genentech
Size
14,000 employees
Industry
Founded
1976

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