Data Scientist, Infrastructure Finance (Technical Leadership)
Sunnyvale, CA | Menlo Park, CA
Meta
Giving people the power to build community and bring the world closer together
Meta is seeking a Data Scientist to join a newly formed team in the Finance organization that partners very closely with Product, AI, Infrastructure, Finance and other Data Science teams across the company. These teams are building some of the most cutting edge and transformative AI products in the world that are being rolled out to Meta’s 3 Billion+ users. Building these products and features requires tens of billions of dollars of capital each year over a sustained period of time. Managing and optimizing the deployment of this vast capital and the allocation of these resources requires a team that has technical expertise in AI and Infrastructure along with a solid understanding of data science, finance and operations. We are building this team in recognition of the importance of AI and Infrastructure from a product perspective as well as the need to be efficient in our approach to deploying capital and generating returns for our shareholders.
This position will use data and analysis to identify and solve product development's biggest challenges and will require one to understand the technical aspects of how AI and Infrastructure are built, operated and used to serve users. This role will help establish the ROI and company-wide prioritization of such investments and work on solving some of the most important technological problems of our times and also ensure that the company makes efficient investments.
As an individual contributor, you will influence product strategy and investment decisions with data, be focused on impact, and collaborate with other teams. By joining Meta, you will become part of a world-class analytics community dedicated to skill development and career growth in analytics and beyond.Data Scientist, Infrastructure Finance (Technical Leadership) Responsibilities
$206,000/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.
Equal Employment Opportunity Meta is proud to be an Equal Employment Opportunity employer. We do not discriminate based upon race, religion, color, national origin, sex (including pregnancy, childbirth, reproductive health decisions, or related medical conditions), sexual orientation, gender identity, gender expression, age, status as a protected veteran, status as an individual with a disability, genetic information, political views or activity, or other applicable legally protected characteristics. You may view our Equal Employment Opportunity notice here.
Meta is committed to providing reasonable accommodations for qualified individuals with disabilities and disabled veterans in our job application procedures. If you need assistance or an accommodation due to a disability, fill out the Accommodations request form.
This position will use data and analysis to identify and solve product development's biggest challenges and will require one to understand the technical aspects of how AI and Infrastructure are built, operated and used to serve users. This role will help establish the ROI and company-wide prioritization of such investments and work on solving some of the most important technological problems of our times and also ensure that the company makes efficient investments.
As an individual contributor, you will influence product strategy and investment decisions with data, be focused on impact, and collaborate with other teams. By joining Meta, you will become part of a world-class analytics community dedicated to skill development and career growth in analytics and beyond.Data Scientist, Infrastructure Finance (Technical Leadership) Responsibilities
- Work with large and complex data sets to solve a wide array of challenging problems using different analytical and statistical approaches
- Apply technical expertise with quantitative analysis, experimentation, data mining, and the presentation of data to build and maintain end-to-end models for long range planning and strategic decisions
- Build models to compute and explain Infrastructure OPEX and CAPEX costs at the company, product and resource levels
- Leverage understanding of AI and Infrastructure to develop independent point-of-view on ROI of investments in Infrastructure and allocation of Infrastructure resources to various products and software platforms
- Identify and measure success infrastructure investments through goal setting, forecasting, and monitoring of key metrics to understand trends
- Help define resource allocation policies that are reasonable and actionable from a technical, operational and financial perspective
- Work with product, engineering and data science teams to do technical, operational and business impact assessments of reallocation of resources based on changing business needs, competitive landscape and product roadmaps
- Maintain lineage of decisions around Infrastructure investments and assumptions under which those decisions were made to drive accountability for outcomes across the company
- Define, understand, and test opportunities and levers to improve our models, and drive roadmaps through your insights and recommendations
- Partner with Product, Engineering, and cross-functional teams to inform, influence, support, and execute product strategy and investment decisions
- Bachelor's degree in a directly related field, or equivalent practical experience
- A minimum of 12 years of work experience in analytics (minimum of 8 years with a Ph.D.)
- Bachelor's degree in Mathematics, Statistics, a relevant technical field, or equivalent practical experience
- Experience with data querying languages (e.g., SQL), scripting languages (e.g., Python), and/or statistical/mathematical software (e.g., R)
- Master's or Ph.D. degree in a quantitative field
- Experience working in a data science role at a hyperscaler, public cloud, and/or a customer of a public cloud company
- Experience partnering cross-functionally with a wide range of teams, deal with ambiguity and present technical content in an easy to understand manner to technical and non-technical teams
- Curiosity about the inter-relationship between business outcomes and technology investments and experience translating this to practical models for decision making
$206,000/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.
Equal Employment Opportunity Meta is proud to be an Equal Employment Opportunity employer. We do not discriminate based upon race, religion, color, national origin, sex (including pregnancy, childbirth, reproductive health decisions, or related medical conditions), sexual orientation, gender identity, gender expression, age, status as a protected veteran, status as an individual with a disability, genetic information, political views or activity, or other applicable legally protected characteristics. You may view our Equal Employment Opportunity notice here.
Meta is committed to providing reasonable accommodations for qualified individuals with disabilities and disabled veterans in our job application procedures. If you need assistance or an accommodation due to a disability, fill out the Accommodations request form.
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Categories:
Data Science Jobs
Leadership Jobs
Tags: Data Mining Engineering Finance Mathematics Physics Python R SQL Statistics VR
Perks/benefits: Career development Competitive pay Equity / stock options Health care Salary bonus
Region:
North America
Country:
United States
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