Meta Platforms, Inc. (Meta) is looking to solve product and business problems by leveraging data and analysis to identify and solve product development's biggest challenges, shape product strategy, quantify new opportunities, and ensure products bring value to people, businesses, and Meta.
Requirements
- Performing quantitative analysis including data mining on highly complex data sets
- Data querying language(s) including SQL
- Scripting language(s) including Python
- Statistical or mathematical software including one of the following: R, SAS, or Matlab
- Applied statistics or experimentation, such as A/B testing, in an industry setting
- Machine learning techniques
- Quantitative analysis techniques, including one of the following: clustering, regression, pattern recognition, or descriptive and inferential statistics
Responsibilities
- Use data and analysis to identify and solve product development’s biggest challenges.
- Use data to shape product development, quantify new opportunities, identify upcoming challenges, and ensure the products we build bring value to people, businesses, and Meta.
- Focus on developing hypotheses and employ a diverse toolkit of rigorous analytical approaches, different methodologies, frameworks, and technical approaches to test them.
- Work with large and complex data sets to solve a wide array of challenging problems using different analytical and statistical approaches.
- Apply technical expertise with quantitative analysis, experimentation, data mining, and the presentation of data to develop strategies for our products that serve billions of people and hundreds of millions of businesses.
- Identify and measure success of product efforts through goal setting, forecasting, and monitoring of key product metrics to understand trends.
- Define, understand, and test opportunities and levers to improve the product, and drive roadmaps through your insights and recommendations.
Other
- Collaborate 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.
- Influence product strategy and investment decisions with data, be focused on impact, and collaborate with other teams.
- Help partner teams prioritize what to build, set goals, and understand their product’s ecosystem.
- Guide teams using data and insights.
- Convince and influence your partners using clear insights and recommendations.
