Job Description

Locations

• South San Francisco

Salary

Skills Required

• pharmaceuticalintermediate
• commercial pharmaceutical analytics lifecycle is requiredintermediate
• modern dataintermediate

Required Qualifications

• Pharma Commercial Analytics/Data Science: Minimum 14+ years of progressive leadership experience in pharmaceutical or national healthcare payer commercial, medical and/or access analytics, marketing science, or data science. Deep domain knowledge of the commercial pharmaceutical analytics lifecycle is required. (experience, 14 years)
• Education: Bachelor’s degree in a quantitative, scientific, or analytical discipline (e.g., Data Science, Statistics, Marketing Analytics, Business Analytics, Economics, Engineering, or Life Sciences). Advanced degree (Master’s or Ph.D.) preferred. (degree in a quantitative)
• Hands-On Analytical Product Expertise: Proven track record in building, operationalizing, and measuring commercial analytics capabilities at scale in healthcare. (experience)
• Domain Expertise: Experience with modern data and AI ecosystems, including platforms such as Databricks, Dataiku, Snowflake, Collibra, Ataccama, Immuta, Reltio, Power BI, and GenAI/AI-ML technologies. (experience)
• Governance: Strong understanding of product management standards, governance, funding models, operating models, adoption, and value realization for enterprise data products. (experience)
• Project Management & Operational Excellence: Proven experience leading enterprise data and analytical product portfolios, setting roadmaps, prioritizing investments, and translating strategy into measurable outcomes. (experience)
• Executive Communication: Outstanding ability to translate complex methodologies and quantitative models into clear, actionable business insights for executive leadership. (experience)
• Pharma Commercial Analytics/Data Science: Minimum 14+ years of progressive leadership experience in pharmaceutical or national healthcare payer commercial, medical and/or access analytics, marketing science, or data science. Deep domain knowledge of the commercial pharmaceutical analytics lifecycle is required. (experience, 14 years)
• Education: Bachelor’s degree in a quantitative, scientific, or analytical discipline (e.g., Data Science, Statistics, Marketing Analytics, Business Analytics, Economics, Engineering, or Life Sciences). Advanced degree (Master’s or Ph.D.) preferred. (degree in a quantitative)
• Hands-On Analytical Product Expertise: Proven track record in building, operationalizing, and measuring commercial analytics capabilities at scale in healthcare. (experience)
• Domain Expertise: Experience with modern data and AI ecosystems, including platforms such as Databricks, Dataiku, Snowflake, Collibra, Ataccama, Immuta, Reltio, Power BI, and GenAI/AI-ML technologies. (experience)
• Governance: Strong understanding of product management standards, governance, funding models, operating models, adoption, and value realization for enterprise data products. (experience)
• Project Management & Operational Excellence: Proven experience leading enterprise data and analytical product portfolios, setting roadmaps, prioritizing investments, and translating strategy into measurable outcomes. (experience)
• Executive Communication: Outstanding ability to translate complex methodologies and quantitative models into clear, actionable business insights for executive leadership. (experience)
• This role is based in South San Francisco and domestic relocation benefits are available. Remote work option will not be considered. (experience)
• This role is based in South San Francisco and domestic relocation benefits are available. Remote work option will not be considered. (experience)
• The expected salary range for this position based on the primary location of CA is $236,900 - $439,900 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. (experience)

Responsibilities

• Commercial Data Science Strategy & Leadership
• Analytics Strategy: Define and drive the strategic analytics roadmap for scalable targeting, optimization, and measurement analytical solutions across the entire commercial lifecycle (launch, growth, and mature brands).
• High-Impact Capabilities: Lead the design and deployment of commercial analytics solutions, such as Next Best Action (NBA) engines, dynamic HCP/patient segmentation, marketing mix modeling (MMM), targeting, field sizing, and omnichannel campaign effectiveness.
• Analytical Product Leadership: Direct long-term analytical product investments and balance cross-portfolio trade-offs to ensure analytical tools directly drive commercial growth and brand performance.
• Analytics Strategy: Define and drive the strategic analytics roadmap for scalable targeting, optimization, and measurement analytical solutions across the entire commercial lifecycle (launch, growth, and mature brands).
• High-Impact Capabilities: Lead the design and deployment of commercial analytics solutions, such as Next Best Action (NBA) engines, dynamic HCP/patient segmentation, marketing mix modeling (MMM), targeting, field sizing, and omnichannel campaign effectiveness.
• Analytical Product Leadership: Direct long-term analytical product investments and balance cross-portfolio trade-offs to ensure analytical tools directly drive commercial growth and brand performance.
• Analytics Execution & Operational Excellence
• In-House Model & Capability Building: Direct the development and deployment of advanced analytical methodologies, partnering across the organization to ensure capabilities are tailored directly to business requirements and commercial workflows. Maximize the embedment of AI capabilities into analytics.
• Scalable Business Deployment: Design and scale analytics solutions that support omnichannel engagement, customer segmentation, resource optimization, campaign measurement, field effectiveness, medical engagement, and access strategy.
• In-House Model & Capability Building: Direct the development and deployment of advanced analytical methodologies, partnering across the organization to ensure capabilities are tailored directly to business requirements and commercial workflows. Maximize the embedment of AI capabilities into analytics.
• Scalable Business Deployment: Design and scale analytics solutions that support omnichannel engagement, customer segmentation, resource optimization, campaign measurement, field effectiveness, medical engagement, and access strategy.
• Rigorous Project Delivery: Apply strong project management and operational frameworks to manage a complex portfolio of solutions, ensuring on-time, high-impact delivery across multiple priorities.
• Measurement: Build measurement frameworks for analytics and AI solutions, including success metrics, test-and-learn design, adoption tracking, performance monitoring, and outcome measurement to quantify business, scientific, operational, and patient impact.
• Change Management & Enablement: Drive organization-wide adoption, training, and operational integration of the product operating model so teams actively embed capabilities into their strategic planning and execution.
• Impact Measurement: Establish robust KPIs to measure campaign performance, field force effectiveness, and the quantitative net business impact of deployed analytics.
• Rigorous Project Delivery: Apply strong project management and operational frameworks to manage a complex portfolio of solutions, ensuring on-time, high-impact delivery across multiple priorities.
• Measurement: Build measurement frameworks for analytics and AI solutions, including success metrics, test-and-learn design, adoption tracking, performance monitoring, and outcome measurement to quantify business, scientific, operational, and patient impact.
• Change Management & Enablement: Drive organization-wide adoption, training, and operational integration of the product operating model so teams actively embed capabilities into their strategic planning and execution.
• Impact Measurement: Establish robust KPIs to measure campaign performance, field force effectiveness, and the quantitative net business impact of deployed analytics.
• People & Team Leadership
• Team Development: Build, direct, and retain a high-performing team with deep expertise in pharma analytics, product development, and commercial execution.
• Commercial Integration: Foster an agile team culture focused on applied analytics and commercial impact.
• Team Development: Build, direct, and retain a high-performing team with deep expertise in pharma analytics, product development, and commercial execution.
• Commercial Integration: Foster an agile team culture focused on applied analytics and commercial impact.

Benefits

• general: 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.
• general: 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.

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