Infrastructure Finance Data Jobs

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Data Scientist, Infrastructure Finance

Meta Menlo Park, CA

Menlo Park, CA

Today

$210k - $281k/yr Full time Data Data Analysis Data Analytics

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Job Description

Meta is seeking an experienced Data Scientist to support Infrastructure Finance. The role will build analysis, models, and decision frameworks that connect planning, financial models, and utilization data to capacity planning and operational practice, with cross-functional partnership to improve the cost and ROI of infrastructure investments.

Responsibilities

Develop and own analytical models and decision frameworks that convert utilization, demand, performance, cost, and capacity constraints into metrics and scenarios for 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 to 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

Requirements

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, including 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 or redesign workflows and drive measurable impact, such as efficiency gains or quality improvements
Experience adhering to and implementing responsible, ethical AI practices, including risk assessment, bias mitigation, and quality and accuracy reviews
Demonstrated ongoing AI skill development, including prompt or context engineering and 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 data center, semiconductor, cloud, server, networking, and software system architecture

Skills and Tools

SQL
Python

Role Location and Compensation

Location: Menlo Park, CA (onsite)

Compensation: USD 210,000 - 281,000 per year

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