AI & Insights - Sr. Manager

Genentech•Daly City, CA

1d•Onsite

About The Position

A healthier future. It’s what drives us to innovate. To continuously advance science and ensure everyone has access to the healthcare they need today and for generations to come. Creating a world where we all have more time with the people we love. The Opportunity: This role leads the development and scaling of AI and advanced analytics capabilities within Digital Finance, enabling more predictive insights, robust scenario modeling, and stronger decision intelligence across the organization. With an enterprise-wide impact on financial performance, the position focuses on turning data into actionable insights that support faster, more informed decision-making. The role balances strategic capability building with hands-on oversight of analytics delivery, while driving innovation through the adoption of modern, data-driven approaches that enhance the effectiveness and agility of the finance function.

Requirements

Education: Bachelor’s degree in Data Science, Statistics, Finance, Engineering, or a related field; Master’s degree in Analytics, Data Science, or MBA preferred.
Experience: 8–12+ years of experience in analytics or finance data leadership roles.
AI/ML delivery: Proven track record of delivering multiple AI/ML solutions into production environments.
Team leadership: Experience managing and developing analytics or data science teams.
Model governance: Familiarity with model risk management frameworks and governance standards.
Technical skills: Strong foundation in statistical modeling and predictive analytics, with working knowledge of SQL and Python.
Communication: Ability to translate complex analyses into clear, compelling insights for executive audiences.
Ethics & mindset: Understanding of ethical AI principles, with a responsible and risk-aware approach to model development and deployment.

Responsibilities

Identify and prioritize AI/ML use cases that deliver measurable business value across finance and enterprise decision-making.
Lead analytics and data science talent, building a high-performing team focused on impact, quality, and scalability.
Define model governance standards covering development, validation, deployment, and lifecycle management.
Translate insights into action by converting complex analytical outputs into clear, executive-ready narratives.
Partner with Data Engineering to ensure models are effectively deployed into production environments and integrated into workflows.
Monitor model performance and risk, including accuracy, bias, drift, and compliance considerations.
Collaborate with senior stakeholders (CFO, USFLT, Global Finance Analytics, RDT Data Engineering) to align on priorities and drive adoption.
Influence cross-functional decisions by using data-driven insights to inform strategy and operational trade-offs.
Support proactive issue identification, leveraging analytics to detect trends, risks, and potential conflicts early.
Build team capability and culture, developing data literacy across finance while coaching analytics talent and fostering strong business translation skills.