Data Scientist, Analytics

About the Role

Key Responsibilities

• Collaborate with a wide array of product and business problems with a diverse set of cross-functional partners across Product, Engineering, Research, Data Engineering, Marketing, Sales, Finance, and others.
• Use data and analysis to identify and solve product development's biggest challenges.
• Influence product strategy and investment decisions with data, focusing on impact, and collaborate with other teams.
• Use data to shape product development, quantify new opportunities, identify upcoming challenges, and ensure the products built bring value to people, businesses, and Meta.
• Help partner teams prioritize what to build, set goals, and understand their product's ecosystem.
• Guide teams using data and insights.
• Focus on developing hypotheses and employ a diverse toolkit of rigorous analytical approaches, methodologies, frameworks, and technical approaches to test them.
• Convince and influence partners using clear insights and recommendations.
• Build credibility through structure and clarity, and be a trusted strategic partner.
• Work with large and complex data sets to solve challenging problems using different analytical and statistical approaches.
• Apply technical expertise with quantitative analysis, experimentation, data mining, and data presentation to develop strategies for products serving billions of people and hundreds of millions of businesses.
• Identify and measure success of product efforts through goal setting, forecasting, and monitoring key product metrics to understand trends.
• Define, understand, and test opportunities and levers to improve the product, and drive roadmaps through insights and recommendations.
• Partner with Product, Engineering, and cross-functional teams to inform, influence, support, and execute product strategy and investment decisions.

Requirements

• A Master's degree in Operations Research, Computer Science, Engineering, or a related field.
• 24 months of experience in the job offered or a related occupation.
• Experience performing quantitative analysis including data mining on highly complex data sets.
• Proficiency with data querying languages including SQL.
• Experience with scripting languages including Python.
• Experience with statistical or mathematical software such as R, SAS, or Matlab.
• Experience with applied statistics or experimentation, such as A/B testing, in an industry setting.
• Knowledge of machine learning techniques.
• Experience with ETL (Extract, Transform, Load) processes.
• Familiarity with relational databases.
• Knowledge of quantitative analysis techniques, including clustering, regression, pattern recognition, or descriptive and inferential statistics.

Qualifications

• Master's degree in Operations Research, Computer Science, Engineering, or a related field.
• 24 months of relevant experience.