Data Scientist, Technical Lead - Infrastructure Data Center (IDC)

Meta•Menlo Park, CA

37d

About The Position

The Infrastructure Data Center (IDC) organization at Meta is looking for an exceptional and highly experienced technical leader to join our Data Science team as the most senior individual contributor and technical authority for Data Science within IDC. This role reports directly to the Head of IDC Data Science. You will define the technical strategy for the organization, drive critical, high-impact data science initiatives across the entire Data Center and Infrastructure domain, and act as a principal storyteller, bridging complex technical concepts with critical business outcomes for leadership and company-wide audiences. This role is crucial for establishing and maintaining how data science is supporting and enabling IDC in the evolving AI landscape.

Requirements

10+ years of experience in a Data Science, Applied Science, or Analytical Engineering role, with a proven track record of leading large, complex technical programs
Exceptional technical background in Data Science, Machine Learning, and statistical methods, demonstrated through industry experience and/or advanced education
Extensive experience working in the Data Center, Infrastructure, Cloud, or other relevant hyperscaler domains, demonstrating deep domain knowledge
Demonstrated ability to function as a technical storyteller, articulating highly technical concepts and their business implications effectively to technical, business, and executive audiences
Proven experience driving technical strategy and thought leadership in a fast-paced, high-growth, and rapidly evolving technical environment, particularly adapting to new AI paradigms
Expertise in programming and querying languages (e.g., Python, R, SQL) and experience working with large-scale data systems
B.S. or M.S. in a quantitative field such as Computer Science, Engineering, Mathematics, Statistics, Physics, or equivalent practical experience
Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience

Nice To Haves

Ph.D. in a quantitative field such as Computer Science, Engineering, Mathematics, Statistics, Physics, or equivalent
Prior experience in a Staff or Principal level individual contributor role, serving as the most senior technical voice for a large organization or domain
Expertise in capacity planning, reliability engineering, energy management, or supply chain optimization within an Infrastructure or Data Center environment
Experience in representing a technical organization externally at conferences, industry working groups, or through publications

Responsibilities

Serve as the foremost technical authority and individual contributor for Data Science within the IDC organization, setting technical direction, standards, and best practices.
Lead the development and execution of technical solutions for high-priority IDC initiatives, particularly those leveraging advanced AI, Machine Learning, and foundational Data Science techniques.
Represent IDC Data Science and the broader IDC organization in high-stakes technical and engineering discussions with a wide range of cross functional partners, including Infra leadership and other Meta organizations.
Act as a technical thought leader, driving innovation in Data Science, Engineering, and analytics specifically tailored to the unique challenges of Data Center and Infrastructure at a hyperscale level.
Translate complex technical work into clear, compelling narratives for diverse audiences, demonstrating the business impact of Data Science initiatives to both technical and executive stakeholders.
Proactively adapt the team's technical roadmap and capabilities to incorporate the latest developments in AI, both ensuring IDC remains at the cutting edge of AI enabling infrastructure and how AI is being leveraged to significantly increase productivity and effectiveness of the team’s work product.
Provide deep technical mentorship and guidance to other Data Scientists and Engineers, raising the overall technical bar of the organization.
Collaborate with Engineering and Product teams to drive the full lifecycle of data science solutions, from ideation and experimentation to robust deployment and measurement at scale.