Data Scientist, Finance (Infrastructure & AI)

Meta; Menlo Park (CA); Hybrid; USD 210,000 - 281,000; Full time

Benefits offered by this job

Equity

Bonus program

Benefits

Job summary

Meta is seeking a data science leader to shape data-driven financial strategy across infrastructure and AI. You will translate advanced modeling into decisions guiding company-wide investments, resource allocation, pricing, and long-term planning.

You will work with finance, infrastructure, and product teams, including Meta Superintelligence Labs, to size opportunities and deliver clear recommendations to senior leaders.

Qualifications

• 12+ years of experience applying statistical and quantitative analysis techniques to drive key business and financial decisions.
• Strong applied statistics and quantitative modeling: experimentation, causal inference / econometrics, uncertainty quantification, forecasting, and scenario modeling.
• Experience communicating data-driven recommendations to executive stakeholders through written and verbal presentations, with a track record of influencing cross-functional decisions.

Responsibilities

• Develop and own analytical models and frameworks informing multi-year infrastructure planning and financial strategy across Meta's AI businesses.

Skills

Statistical analysis

Quantitative modeling

Causal inference

Forecasting

Scenario modeling

Executive communication

SQL

Python

Tools

SQL

Python

Job description

Meta is seeking a data science leader to shape data-driven financial strategy across infrastructure and AI. You'll translate advanced modeling into decisions that guide company-wide investment, resource allocation, pricing, and long-term planning, helping leaders act under significant uncertainty. You'll work closely with cross-functional partners across finance, infrastructure, and product teams, including Meta Superintelligence Labs (MSL).The ideal candidate combines strong analytical skills with business acumen — someone who can navigate ambiguous, early-stage problem spaces, identify where Meta can deploy resources more efficiently or improve pricing and monetization, and translate those insights into quantified opportunities and clear recommendations.Data Scientist, Finance (Infrastructure & AI) Responsibilities:Develop and own analytical models and frameworks that inform multi-year infrastructure planning, investment prioritization, and the financial strategy of Meta's AI businessesBuild frameworks to evaluate ROI on compute, infrastructure, data, and related spend across products, features, and business segments, and use those insights to inform investment and resource-allocation decisionsDevelop a rigorous understanding of the unit economics of Meta's AI products and business models — contribution margin, cost-to-serve, marginal cost, lifetime value, and the trade-offs that drive them — to inform strategy, pricing, and monetizationIndependently identify efficiency, financial, and monetization opportunities — surfacing where Meta can get more from its investments — and rapidly build the analysis to size and pressure-test them, operating with minimal guidance in ambiguous problem spacesPartner with finance, infrastructure, and product teams (including MSL) to define success metrics, size financial opportunities, align on technical methodology, and evaluate trade-offs across competing strategic prioritiesSynthesize data into clear, business-relevant recommendations and communicate their implications to VPs and executive stakeholdersDesign rigorous research and hypothesis-testing approaches, and oversee the quality of analytical outputs across finance, infrastructure, and AI-business domainsIdentify and drive adoption of AI-integrated analytics workflows, including orchestrating AI tools to accelerate modeling and analysisLead ad hoc analyses of emerging topics critical to Meta's business and financial strategyMinimum Qualifications:12+ years of experience applying statistical and quantitative analysis techniques to drive key business and financial decisionsExperience shaping and influencing strategy, investment, or monetization decisions — for example in infrastructure, product economics, pricing, or the economics of AI / technology businessesStrong applied statistics and quantitative modeling: experimentation, causal inference / econometrics, uncertainty quantification, forecasting, and scenario modelingDemonstrated business and economics intuition — a strong grasp of contribution margin, cost-to-serve, ROI, and trade-offs — and a track record of independently identifying financial or efficiency opportunities and driving them to measurable outcomes in ambiguous, fast-moving environmentsExperience communicating data-driven recommendations to executive stakeholders through written and verbal presentations, with a track record of influencing cross-functional decisions without direct authorityExperience coding in SQL and Python (or equivalent) to independently work through large, messy datasets and to build, maintain, and optimize analytical models at production scalePreferred Qualifications:Familiarity with AI/compute cost economics — understanding inference and training cost drivers well enough to translate technical changes into $/token and marginExperience with pricing and demand modeling (elasticity, willingness to pay, packaging, subscription/API pricing) and translating analysis into pricing and monetization recommendationsExperience adhering to and implementing responsible, ethical AI practices (e.g., risk assessment, bias mitigation, quality and accuracy reviews)Demonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologiesDemonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements)Experience in data science and/or driving strategy at a hyperscaler, frontier AI lab, or large technology companyAbout Meta:Meta builds technologies that help people connect, find communities, and grow businesses. When Facebook launched in 2004, it changed the way people connect. Apps like Messenger, Instagram and WhatsApp further empowered billions around the world. Now, Meta is moving beyond 2D screens toward immersive experiences like augmented and virtual reality to help build the next evolution in social technology. People who choose to build their careers by building with us at Meta help shape a future that will take us beyond what digital connection makes possible today—beyond the constraints of screens, the limits of distance, and even the rules of physics.Meta is proud to be an Equal Employment Opportunity and Affirmative Action employer. We do not discriminate based upon race, religion, color, national origin, sex (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender, gender identity, gender expression, transgender status, sexual stereotypes, age, status as a protected veteran, status as an individual with a disability, or other applicable legally protected characteristics. We also consider qualified applicants with criminal histories, consistent with applicable federal, state and local law. Meta participates in the E-Verify program in certain locations, as required by law. Please note that Meta may leverage artificial intelligence and machine learning technologies in connection with applications for employment.Meta is committed to providing reasonable accommodations for candidates with disabilities in our recruiting process. If you need any assistance or accommodations due to a disability, please let us know at [e-mail].$210,000/year to $281,000/year + bonus + equity + benefitsIndividual compensation is determined by skills, qualifications, experience, and location. Compensation details listed in this posting reflect the base hourly rate, monthly rate, or annual salary only, and do not include bonus, equity or sales incentives, if applicable. In addition to base compensation, Meta offers benefits. Learn more about benefits at Meta.