Data Scientist, Infrastructure Finance

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

Job summary

Meta seeks an experienced data scientist to improve how we plan, utilize, and drive ROI from large-scale infrastructure. You will build models and decision frameworks that connect planning, financial models, and utilization data to capacity planning and operational practice, helping leaders improve cost and ROI of compute, storage, data centers, and power investments.

The role sits at the intersection of data science, finance, and infrastructure planning, partnering with Infrastructure Planning,

Qualifications

• Bachelor's degree in a directly related field or equivalent practical experience.
• Degree in a quantitative field (Engineering, Math, Science) or equivalent practical experience.
• 10+ years of experience applying analysis, data science, statistics, economics, or operations research to business decisions.
• Experience applying data science to operational planning, resource allocation, or efficiency decisions and translating models into decision tools (including spreadsheets).
• Experience using SQL and Python to analyze large datasets and build reusable models.
• Experience communicating quantitative recommendations to executives and influencing decisions across organizations.

Responsibilities

• Develop analytical models and decision frameworks translating utilization, demand, cost, and capacity into metrics for multi-year capacity plans and investment priorities.
• Identify, size, and pressure-test utilization and efficiency opportunities in ambiguous problem spaces.
• Partner with Planning, Capacity Engineering, and Operations to embed recommendations into planning and reviews.
• Align data definitions, analytical methods, and financial implications with Finance teams and establish model validation standards.
• Synthesize complex analysis into clear recommendations for VP and executives, influencing cross-functional decisions without direct authority.

Skills

SQL

Python

Data analysis

Econometrics

Operations research

Stakeholder communication

Education

Bachelor's degree in a directly related field

Degree in a quantitative field (Engineering, Math, Science) or equivalent practical experience

Job description

Meta is seeking an experienced data scientist to improve how we plan, utilize and drive ROI from large-scale infrastructure. You will build analysis, models and decision frameworks that connect planning, financial models, and utilization data to capacity planning and operational practice, helping leaders improve the cost and ROI of Meta's compute, storage, data center, and power investments.This role sits at the intersection of data science, finance, and infrastructure planning. You will partner with Infrastructure Planning, Capacity Engineering, Infrastructure Data Science, Infrastructure Finance, and Product Finance to turn technical and operational signals into clear investment and operating decisions.

Data Scientist, Infrastructure Finance Responsibilities:

• Develop and own analytical models and decision frameworks that translate utilization, demand, performance, cost, and capacity constraints into metrics and scenarios that inform multi-year capacity plans, investment priorities, and efficiency goals
• Independently identify, size, and pressure-test utilization and efficiency opportunities in ambiguous problem spaces
• Partner with Infrastructure Planning, Capacity Engineering, and Operations to embed recommendations into planning assumptions, goals, and operating reviews
• Partner with Infrastructure Data Science, Infrastructure Finance, and Product Finance to align data definitions, analytical methods, and financial implications, and set standards for model validation, documentation, auditability, and reproducibility
• Synthesize complex analysis into clear recommendations for VP and executive stakeholders, influencing cross-functional decisions without direct authority

Minimum Qualifications:

• Bachelor's degree in a directly related field, or equivalent practical experience
• Degree in a quantitative field (Engineering, Math, Science) or equivalent practical experience
• 10+ years of experience applying analysis, data science, statistics, economics, or operations research to business and investment decisions
• Experience applying data science to operational planning, resource allocation, or efficiency decisions and carrying ambiguous work from problem definition through implementation and measurable outcome
• Experience translating scenario and sensitivity models into decision tools used by business partners, including spreadsheets
• Experience using SQL and Python, or equivalent tools, to independently analyze large, messy datasets and build, maintain, and improve reusable analytical models
• Experience communicating quantitative recommendations to executives and influencing decisions across organizations

Preferred Qualifications:

• Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements)
• Experience 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 technologies
• Experience evaluating ROI, marginal cost, cost-to-serve, and capital-allocation trade-offs
• Demonstrated use of AI tools to accelerate analytical workflows and improve work quality, with responsible practices for validation, reproducibility, and sensitive-data handling
• Experience with forecasting, scenario modeling, uncertainty quantification, and causal inference or econometrics
• Experience with infrastructure planning, capacity engineering, operations, cloud or compute economics, or other capital-intensive systems
• Familiarity with AI infrastructure economics and data center constraints, including training and inference cost drivers, accelerator utilization, power, and cost-performance-utilization trade-offs across CPUs, GPUs, and storage
• Familiarity with concepts in data center, semiconductor, cloud, server, networking, and software system architecture

About 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 AffirCmp 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 + benefits

Individual 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.