Data Scientist at Meta
Bellevue, WA 98005, USA -
Full Time


Start Date

Immediate

Expiry Date

17 Oct, 25

Salary

204000.0

Posted On

17 Jul, 25

Experience

2 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

No

Skills

Cleansing, Data Center Operations, Data Modeling, Spark, Computer Science, Experimental Design, Statistics, Teams, Mathematics, R, Tableau, Presto, Learning Techniques, Python, Engineers, Algorithms, Nlp, Optimization, Data Processing, Computer Engineering

Industry

Information Technology/IT

Description

DATA CENTER OPERATIONS

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, 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 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. This position is part of the Infrastructure Data Centers organization.

MINIMUM QUALIFICATIONS

  • Bachelor’s degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience.
  • 6+ years of experience (2 years+ of experience post Ph.D.) with advanced SQL in big data environments (e.g., Hive, Presto, Spark) and data modeling.
  • 6+ years of experience (2 years+ of experience post Ph.D.) managing and analyzing large-scale data using Python, R, or similar languages.
  • 6+ years of experience (2 years+ of experience post Ph.D.) of working with visualization tools such as Tableau, PowerBI, or similar.
  • 6+ years 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

  • Technical knowledge of data center operations
  • Masters degree in Computer Science, Engineering, Mathematics, Statistics, Operations Research, or a related analytical field.
  • Knowledge of simulation and optimization techniques
  • Great communication and storytelling skills to influence all organizational levels (engineers, executives and cross functional teams) to drive business decisions
    For those who live in or expect to work from California if hired for this position.
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.
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