Senior Manager AI and Analytics - Finance

Intuitive•Sunnyvale, CA

2d•$162,500 - $286,800•Onsite

About The Position

The Senior Manager AI and Analytics - Finance serves as an anchor for Intuitive’s Enterprise Analytics team and partners with 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 on ongoing initiatives, and guides and oversees financial data products that support the Finance organization. The position leads a direct team spanning analytics engineering (architects and analysts) and AI product management, and provides dotted-line leadership to the Finance data engineering team. It works closely with Finance leadership, enterprise data architects, data engineering, and external service providers to ensure capabilities meet business needs. The role manages a portfolio of analytics and AI initiatives, establishes governance and scalable operating processes, measures business impact, and supports adoption and data literacy across Finance.

Requirements

Bachelor's degree in Computer Science, Information Systems, Business Management, Data Science, or a related field, or equivalent work experience.
7+ years of progressive experience in analytics, business intelligence, data warehousing, or data product management.
3+ years leading and developing teams of analytics, AI, or technical professionals, directly or through matrixed/dotted-line leadership.
Proven experience 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 tools.
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 translate complex technical concepts into business language for senior leaders.
Ability to influence without direct authority across cross-functional teams and senior stakeholders.
Skill translating business needs into technical roadmaps and driving alignment between 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

Manage the analytics portfolio and Finance business-partner relationships, including intake, prioritization, replanning, regular reviews, project tracking, objectives and KPIs, stakeholder alignment, and risk management for quality, schedule, and budget.
Own and drive the Finance AI product roadmap, prioritizing and sequencing AI/ML initiatives in partnership with Finance and IT leadership.
Serve as AI product manager on active initiatives, translating business needs into AI-enabled solutions and guiding them from concept through delivery.
Lead and develop a direct team of analytics engineering architects and analysts and AI product managers; provide dotted-line leadership to the Finance data engineering team and align priorities and ways of working.
Guide resource allocation and budget management by synthesizing operational and financial data to optimize team capacity and investment priorities.
Design and implement scalable processes, frameworks, and tooling to improve coordination and operational efficiency across analytics and data engineering teams.
Establish and maintain portfolio governance that provides transparency into progress, risks, and value delivery across active workstreams.
Promote knowledge sharing and adoption through documentation, playbooks, and communication channels that enable Finance and cross-functional teams to self-serve analytics capabilities.
Present to senior leaders and executives and facilitate decisions based on evolving priorities.
Collaborate with insights architects and data engineering to design data standards and data products that support business organizations.
Standardize key metrics across business stakeholders to improve data governance maturity.
Define and track measurable ROI and business impact for AI/ML initiatives, giving 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 vendor and external service-provider relationships, including contract oversight, performance evaluation, and alignment with internal delivery standards.