Data Scientist

Meta is seeking a skilled and motivated Data Scientist to join our Infrastructure Data Centers team. As a lead data scientist, you will partner with stakeholders, program managers, and other data science functions to translate Meta’s Infrastructure Data Centers’ data into value. You will have the opportunity to work on a wide range of data science projects, such as developing an analytics program to drive operational efficiency, conducting strategic analysis to facilitate decision making, measuring Machine Learning models and automation to increase predictive accuracy and reduce manual effort, and working with software developers to build analytical solutions.

The ideal candidate will have experience defining scope and driving outcomes in environments with evolving requirements. Additionally, you will have a proven track record of developing and delivering analytics programs that drove measurable business impact in developing similar analytics programs and machine learning solutions. This position is part of the Infrastructure Data Centers organization.

Data Scientist Responsibilities:

Collaborate with cross-functional data and business teams to define problems, analyze impacts, identify opportunities, and develop solutions that improve decision-making and efficiency

Translate business challenges into data-driven problems and design appropriate data science solutions, including metrics and analytics, business intelligence, experimentation

Identify operational gaps, build analytical models to derive insights, and support decision-making across organizational leadership

Design and implement statistical models such as hypothesis testing, forecasting, statistical process control, and simulation to influence critical business decisions and Data Center operations

Utilize expertise in statistics, machine learning, optimization, and automation to develop analytics solutions

Work closely with stakeholders, data engineers, and program/product managers to ensure seamless progress

Educate and influence stakeholders to enhance operational efficiency with empathy

Recommend process improvements based on operational data and user behavior to boost business performance

Mentor team members on data science best practices

Minimum Qualifications:

Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience6+ years of experience (2 years+ of experience post Ph.D.) with advanced SQL in big data environments (e.g., Hive, Presto, Spark) and data modeling6+ years of experience (2 years+ of experience post Ph.D.) managing and analyzing large-scale data using Python, R, or similar languages6+ years of experience (2 years+ of experience post Ph.D.) of working with visualization tools such as Tableau, PowerBI, or similar6+ years of experience (2 years+ of experience post Ph.D.) analyzing and interpreting data, developing metrics, drawing conclusions, recommending actions, and reporting results across stakeholders

Experience in enhancing data collection procedures, data processing, cleansing, and verifying the integrity of data used for analysis

Proven track record of managing and leading cross-functional projects and teams

Solid understanding of machine learning techniques and algorithms

Hands-on programming experience in one or more of: AI/ML, LLM, NLP, Statistical modeling

Proficient in statistical analysis and experimental design

Preferred Qualifications:

Knowledge of simulation and optimization techniques

Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements)
Technical knowledge of data center operations

Experience adhering to and implementing responsible, ethical AI practices (e.g., risk assessment, bias mitigation, quality and accuracy reviews)
Great communication and storytelling skills to influence all organizational levels (engineers, executives and cross functional teams) to drive business decisions

Demonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologies

Master's degree in Computer Science, Engineering, Mathematics, Statistics, Operations Research, or a related analytical field

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 Whats App 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.

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