Strategic Finance - Product, AI/ML and Analytics

Reposted 4 Days Ago
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Menlo Park, CA, USA
In-Office
204K-255K Annually
Senior level
Artificial Intelligence • Big Data • Cloud • Machine Learning • Software • Database • Analytics
Let's build a world where data and AI turn possibilities into reality.
The Role
Senior strategic finance partner for AI and Analytics products. Own forecasting, pricing, monetization, investment business cases, KPI/reporting, and lead a small analytics team to guide product, engineering, and GTM decisions.
Summary Generated by Built In

At Snowflake, we are powering the era of the agentic enterprise. To usher in this new era, we seek AI-native thinkers across every function who are energized by the opportunity to reinvent how they work. You don’t just use tools; you possess an innate curiosity, treating AI as a high-trust collaborator that is core to how you solve problems and accelerate your impact. We look for low-ego individuals who thrive in dynamic and fast-moving environments and move with an experimental mindset — who rapidly test emerging capabilities to discover simpler, more powerful ways to deliver results. At Snowflake, your role isn't just to execute a function, but to help redefine the future of how work gets done.

About Snowflake

At Snowflake, we are powering the era of the agentic enterprise. To usher in this new era, we seek AI-native thinkers across every function who are energized by the opportunity to reinvent how they work. You don't just use tools; you possess an innate curiosity, treating AI as a high-trust collaborator that is core to how you solve problems and accelerate your impact. We look for low-ego individuals who thrive in dynamic and fast-moving environments and move with an experimental mindset, who rapidly test emerging capabilities to discover simpler, more powerful ways to deliver results. At Snowflake, your role isn't just to execute a function, but to help redefine the future of how work gets done.

About the Team

Strategic Finance is the commercial and analytical engine behind Snowflake's product and revenue decisions. The team operates at the intersection of product strategy, pricing, and investment prioritization. Product Finance, the function this role sits within, partners with each product organization on planning, performance, and pricing. We work closely with Product and Engineering leadership, and we partner across Sales, Business Development, and the Executive Leadership Team. Every consequential AI and Analytics investment, monetization, and pricing decision at Snowflake runs through analysis this team produces.

About the Role

We are hiring a senior strategic finance thought partner to help shape Snowflake's AI and Analytics workloads, the company's fastest-growing and most strategically complex product surface. You will partner closely with Product, Engineering, Marketing, and Sales leadership to set strategy, evaluate growth bets, lead pricing and packaging decisions, and build the financial rigor that lets these workloads scale.

You will translate product usage, customer behavior, unit economics, and market signals into decisions on what we build, how we launch, how we monetize, and where we invest. You will help define the growth model for a frontier AI product portfolio while working at the intersection of strategy, finance, and technology. This is a people manager role.

In This Role You Will
  • Strategic Finance Thought Partnership. Serve as the strategic finance partner to Cortex, Notebooks, Machine Learning, and Analytics product and engineering leaders. Help shape product strategy, growth priorities, pricing decisions, and investment tradeoffs.

  • Forecast and Performance Ownership. Own the forecast for AI and Analytics workloads, including revenue, usage, margin, unit economics, leading indicators, and the operating metrics that show where each workload is gaining or losing traction.

  • Pricing and Monetization Leadership. Lead pricing and monetization strategy for AI workloads. Set pricing principles, packaging, metering, and commercial terms across inference, training, embedded models, and AI-native applications. Bring willingness-to-pay research, competitive benchmarks, and unit economics into pricing decisions. Land emerging AI commercial structures as they graduate from incubation to scaled go-to-market.

  • Translate Data Into Decisions. Translate product usage, customer behavior, cohort and funnel dynamics, and financial data into clear recommendations that influence long-term strategy and day-to-day product calls.

  • Investment Business Cases. Build decision-ready business cases for major AI and Analytics product and go-to-market investments. Return on investment, investment sizing, risk framing, comparative tradeoffs.

  • Build Planning and Performance Systems. Build the forecast methodology, key performance indicator architecture, decision frameworks, executive narratives, and repeatable reporting that help the team move faster as the workloads scale.

  • People Leadership. Manage and develop a small team of analysts. Set the bar for analytical rigor, executive communication, and product judgment. Cultivate a team that operates as a credible thought partner to Product and Engineering.

  • Market Intelligence. Stay current on AI, software-as-a-service, product-led growth, consumption-based pricing, and competitive dynamics. Inform where Snowflake should invest in AI workloads and how the business model should evolve as AI changes the playbooks.

  • Executive Narratives. Prepare and deliver high-quality executive and Board materials that connect business performance, product strategy, key risks, and strategic recommendations.

What You Will NeedRequired
  • 8+ years of experience in investment banking, management consulting, strategic finance, product finance, growth finance, or buy-side investing, coupled with operating experience at a fast-paced, scaling technology company.

  • Experience supporting product teams on growth, pricing, packaging, monetization, or product strategy decisions, ideally in product-led growth, growth-stage software-as-a-service, consumption-based, or usage-based business models.

  • Exceptional analytical and financial modeling skills, including building product profit and loss views, operating models, cohort and funnel analyses, pricing models, and unit economics that connect strategy to growth decisions.

  • Strong business judgment and product instincts. Ability to evaluate opportunities, tradeoffs, and risks in a fast-moving product environment.

  • Working understanding of AI and machine learning infrastructure and economics: model lifecycle, inference vs. training cost structures, AI commercial models. Curiosity about how AI products change the pricing and packaging playbooks.

  • The ability to translate complex product, usage, customer, and financial data into clear recommendations for Product teams and senior leadership.

  • High attention to detail and a commitment to accuracy, paired with comfort making decisions when data is imperfect and the business is evolving.

  • People management experience. Demonstrated track record of hiring, developing, and retaining strong analytical talent.

  • SQL fluency. Comfort working directly with product analytics datasets in a cloud data platform.

  • Effective communication. Capable of producing executive-quality narratives that survive Executive Leadership Team and Board review on first submission.

  • Bachelor's degree in Finance, Economics, Computer Science, Engineering, or related discipline. MBA preferred.

Preferred
  • Hands-on experience with AI and machine learning product economics at a high-growth company (foundation model provider, AI infrastructure, AI applications, or a major cloud's AI portfolio).

  • Familiarity with consumption-based and usage-based pricing in cloud, data, or AI platforms.

  • Experience building business cases and growth models for new product categories where commercial mechanics are not yet standardized.

  • Experience with competitive AI pricing analysis and willingness-to-pay research.

  • Python proficiency for data analysis.

Location

Menlo Park, CA. Snowflake HQ office. This role requires in-person attendance at least 3 days per week. Location is strict.

Equal Opportunity Statement

Snowflake is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to age, color, gender identity or expression, marital status, national origin, disability, protected veteran status, race, religion, pregnancy, sexual orientation, or any other characteristic protected by applicable laws, regulations and ordinances.

Snowflake is growing fast, and we’re scaling our team to help enable and accelerate our growth. We are looking for people who share our values, challenge ordinary thinking, and push the pace of innovation while building a future for themselves and Snowflake.

How do you want to make your impact?

For jobs located in the United States, please visit the job posting on the Snowflake Careers Site for salary and benefits information: careers.snowflake.com

Skills Required

  • 8+ years of experience in investment banking, management consulting, strategic finance, product finance, growth finance, or buy-side investing with operating experience at a scaling technology company
  • Experience supporting product teams on growth, pricing, packaging, monetization, or product strategy decisions (product-led growth, consumption/usage-based models)
  • Exceptional analytical and financial modeling skills (product P&L, operating models, cohort and funnel analyses, pricing models, unit economics)
  • Working understanding of AI and machine learning infrastructure and economics (model lifecycle, inference vs. training cost structures, AI commercial models)
  • SQL fluency and comfort working directly with product analytics datasets in a cloud data platform
  • People management experience, including hiring, developing, and retaining analytical talent
  • Effective executive communication and ability to produce Board- and ELT-quality narratives
  • Bachelor's degree in Finance, Economics, Computer Science, Engineering, or related discipline
  • Willingness and ability to be in Snowflake HQ (Menlo Park, CA) at least 3 days per week
  • MBA
  • Python proficiency for data analysis
  • Hands-on experience with AI and machine learning product economics at a high-growth company
  • Familiarity with consumption-based and usage-based pricing in cloud, data, or AI platforms
  • Experience building business cases and growth models for new product categories and conducting willingness-to-pay research

Snowflake Compensation & Benefits Highlights

The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Snowflake and has not been reviewed or approved by Snowflake.

  • Fair & Transparent Compensation Pay is considered competitive across many roles, and the company highlights structured practices aimed at pay equity. Total compensation is often described as strong at senior levels when equity and bonuses are included.
  • Equity Value & Accessibility Equity grants and an ESPP are standard, making ownership accessible and a meaningful part of total rewards. New-hire RSUs and ongoing equity alongside bonus/commission programs are emphasized.
  • Healthcare Strength Comprehensive medical coverage is offered with programs like Lyra providing up to 25 no-cost therapy/coaching sessions, alongside HSA-eligible plans. Wellness resources and additional clinical programs (such as Omada for certain conditions) broaden the scope of support.

Snowflake Insights

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The Company
HQ: Bozeman, MT
9,023 Employees
Year Founded: 2012

What We Do

Snowflake powers the end-to-end data lifecycle – from ingesting and processing data to analyzing and modeling it, to building and sharing data and AI applications – helping engineers, analysts, and leaders innovate faster and achieve more with their data. We're on a mission to empower every enterprise to achieve its full potential through data and AI.

Why Work With Us

Snowflake is where data does more, and so do you. More innovating, more growing, and more collaborating. Here, you’ll find the sweet spot between building big and moving fast, in technology and your career.

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