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Data Scientist, Infrastructure Finance (Technical Leadership)

Meta

Menlo Park (CA)

On-site

USD 206,000 - 281,000

Full time

6 days ago
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Job summary

Meta is seeking a Data Scientist for a Technical Leadership role in Infrastructure Finance. The position involves addressing complex investment challenges, utilizing data analysis to influence product strategy, and collaborating across teams to optimize resource allocation. Ideal candidates should have significant experience in analytics and a strong educational background in quantitative fields.

Qualifications

  • 12+ years of work experience in analytics (8+ years with Ph.D.).
  • Experience with data querying, scripting, and statistical software.

Responsibilities

  • Work with large data sets to solve challenging problems.
  • Build models to understand Infrastructure OPEX and CAPEX costs.
  • Collaborate with product and engineering teams on impact assessments.

Skills

Analytical skills
Data mining
Quantitative analysis
Statistical analysis
Technical expertise

Education

Bachelor's degree in Mathematics, Statistics, or related field
Ph.D. in a related field

Tools

SQL
Python
R

Job description

Data Scientist, Infrastructure Finance (Technical Leadership)

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Data Scientist, Infrastructure Finance (Technical Leadership)

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This range is provided by Meta. Your actual pay will be based on your skills and experience — talk with your recruiter to learn more.

Base pay range

$206,000.00/yr - $281,000.00/yr

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:

  • 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

Minimum Qualifications:

  • 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)

Preferred Qualifications:

  • 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

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 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 accommodations-ext@fb.com.

$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.

Seniority level
  • Seniority level
    Not Applicable
Employment type
  • Employment type
    Full-time
Job function
  • Job function
    Engineering and Information Technology
  • Industries
    Technology, Information and Internet

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