Senior Manager AI and Analytics - Finance

Intuitive•Sunnyvale, CA

About The Position

The Senior Manager AI and Analytics - Finance partners with Intuitive’s Finance leadership to strategize, design, and mature analytical and AI capabilities. The role owns the AI product roadmap for Finance, serves as an AI product manager for ongoing initiatives, and guides financial data products in support of the Finance organization. The role leads a direct team of analytics engineering professionals and AI product managers, with dotted-line leadership over the Finance data engineering team. It works with Finance leadership, enterprise data architects, data engineering, and external service providers to deliver capabilities that meet business needs. The position also manages the analytics portfolio, establishes governance and operating processes, supports adoption and data literacy, and communicates progress, risks, and value to senior leaders.

Requirements

Bachelor’s degree in Computer Science, Information Systems, Business Management, Data Science, or a related field, or equivalent work experience.
At least 7 years of progressive experience in analytics, business intelligence, data warehousing, or data product management.
At least 3 years leading and developing teams of analytics, AI, or technical professionals, directly or through matrixed/dotted-line leadership.
A proven record of managing large portfolios of analytics and AI initiatives across multiple stakeholders and competing priorities.
Experience delivering AI/ML-enabled solutions from concept through production, including defining use cases, success criteria, and business value.
Deep Finance domain expertise in FP&A, accounting, controllership, or treasury.
Familiarity with modern data platforms such as Snowflake, ERP systems such as SAP S/4HANA, and CRM platforms such as Salesforce.
Working knowledge of AI/ML tools and platforms, such as Claude, Azure AI Document Intelligence, or similar.
Experience with analytics and visualization tools such as Tableau or Power BI.
Understanding of software development methodologies such as Agile and SDLC, and project/service management tools such as Jira or ServiceNow.
Strong executive communication skills, including the ability to explain complex technical concepts in business terms to senior leaders.
Ability to influence without direct authority across cross-functional teams and senior stakeholders.
Skill in translating business needs into technical roadmaps and aligning business and technology teams.
Strong vendor management capabilities, including oversight of external service providers and delivery partners.

Nice To Haves

Master’s degree preferred.
Experience in Sales or Marketing is a plus.

Responsibilities

Lead the analytics portfolio by managing relationships with Finance business partners, intake and prioritization, replanning, project reviews, objectives and KPIs, stakeholder alignment, and risks to quality, schedule, and budget.
Own and drive the Finance AI product roadmap, prioritizing and sequencing AI/ML initiatives with Finance and IT leadership.
Serve as AI product manager on active initiatives, translating business needs into AI-enabled solutions and leading them from concept through delivery.
Lead and develop a direct team of analytics engineering architects and analysts and AI product managers, while providing dotted-line leadership to the Finance data engineering team.
Drive resource allocation and budget decisions by using operational and financial data to optimize capacity and investment priorities.
Design and implement scalable processes, frameworks, and tools to improve coordination and operational efficiency across analytics and data engineering teams.
Establish and maintain portfolio governance that makes progress, risks, and value delivery visible across active workstreams.
Promote knowledge sharing and adoption through documentation, playbooks, and communication channels that enable Finance and cross-functional teams to self-serve on analytics capabilities.
Present to senior leaders and executives and facilitate decisions in response to evolving priorities.
Collaborate with insights architects and data engineering to design data standards and data products that support business organizations.
Standardize key metrics across stakeholders to improve data governance maturity.
Define and track ROI and business impact for AI/ML initiatives, providing Finance leadership visibility into the value of analytics investments.
Monitor emerging AI/ML technologies, tools, and practices and evaluate their applicability to Finance use cases.
Foster experimentation, continuous learning, and data literacy within Finance.
Manage vendors and external service providers, including contract oversight, performance evaluation, and alignment with internal delivery standards.