Meta is seeking a Lead Data Scientist to join their Infrastructure Data Centers team to translate data into value, drive operational efficiency, facilitate decision making, and increase predictive accuracy through machine learning and automation.
Requirements
- 8+ years of experience (4 years+ of experience post Ph.D.) with advanced SQL in big data environments (e.g., Hive, Presto, Spark) and data modeling
- 8+ years of experience (4 years+ of experience post Ph.D.) managing and analyzing large-scale data using Python, R, or similar languages
- 8+ years of experience (4 years+ of experience post Ph.D.) of working with visualization tools such as Tableau, PowerBI, or similar
- 8+ years experience (4 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
- Solid understanding of machine learning techniques and algorithms
- Hands-on programming experience in one or more of: AI/ML, LLM, NLP, Statistical modeling
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 a seamless progress
- Recommend process improvements based on operational data and user behavior to boost business performance
Other
- Proven track record of managing and leading cross-functional projects and teams
- Educate and influence stakeholders to enhance operational efficiency with empathy
- Mentor team members on data science best practices
- Technical knowledge of data center operations
- Communication and storytelling skills to influence all organizational levels (engineers, executives and cross functional teams) to drive business decisions
