Data Scientist - Meta

Meta is seeking a highly skilled and motivated Data Scientist to join our Infrastructure Data Centers team. As a lead data scientist, you will partner with stakeholders, Product & 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, building 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 a passion for working in ambiguous environment and creating impact from the ground up in a fast-paced environment. Additionally, you will have a proven track record of thought leadership and impact in developing similar analytics programs and machine learning solutions.

RESPONSIBILITIES

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 analytics, business intelligence, experimentation, optimization, AI/ML, and automation.
• 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 Planning & Operations.
• Utilize expertise in machine learning, statistics, and automation to develop analytics solutions.
• Deploy models to production, ensuring they operate reliably and efficiently at a large scale.
• Continuously monitor and update models to adapt to new data or changes in data patterns.
• 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

Minimum Qualifications:

• Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience.
• MS degree in Computer Science, Mathematics, Statistics, Operations Research, or a related field.
• 8+ years of experience managing and analyzing large-scale data using Python, R, or similar languages.
• 8+ years of experience with SQL in big data environments (e.g., Hive, Presto, Spark) and data modeling.
• 8+ years of experience analyzing and interpreting data, developing metrics, drawing conclusions, recommending actions, and reporting results across stakeholders.
• Proven track record of managing and leading cross-functional projects and teams.
• Proven 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

Preferred Qualifications:

• 8+ years of experience in model building and algorithm development for machine learning, statistics, and simulation.
• Experience in putting ML models into production and continuous monitoring and improvement.
• Familiarity with object-oriented programming languages (such as C++ or Java) and visualization tools (such as Tableau)
• Knowledge of simulation and optimization techniques
• Experience with GIS (geographic information systems), including collecting, managing, analyzing, modeling, and presenting geographic or spatial data.