Responsibilities
- Collect, organize, interpret, and summarize statistical data in order to contribute to the design and development of Meta products.
- Apply your expertise in quantitative analysis, data mining, and the presentation of data to see beyond the numbers and understand how our users interact with both our consumer and business products.
- Partner with Product and Engineering teams to derive quantitative understanding of Meta's ML infrastructure and ML applications to inform future strategy and design ML solutions for complex problems.
- Define, understand, and test opportunities and levers to improve the product, and drive roadmaps through your insights and recommendations.
- Inform, influence, support, and execute our product decisions and product launches.
- Build ML prototyping solutions.
- May be assigned projects in various areas including, but not limited to, product operations, exploratory analysis, product influence, and data infrastructure.
- Work on problems of moderate scope where analysis of situations or data requires a review of a variety of factors.
- Exercise judgment within defined procedures and practices to determine appropriate action.
Minimum Qualifications
- Requires a Bachelor's degree (or foreign degree equivalent) in Statistics, Mathematics, Data Analytics, Computer Science, Engineering, Information Systems, Applied Sciences, or an engineering-related field and 2 years of experience in the job-offered or in a computer-related occupation
- Requires 2 years of experience in the following:
- Performing quantitative analysis including data mining on highly complex data sets
- Data querying language: SOL
- Scripting language: Python
- Statistical or mathematical software including one of the following: R, SAS, or Matlab
- Applied statistics or experimentation, such as A/8 testing, in an industry setting
- Machine learning techniques
- ETL (Extract, Transform, Load) processes
- Relational databases
- Large-scale data processing infrastructures using distributed systems
- Quantitative analysis techniques, including one of the following: clustering, regression, pattern recognition, or descriptive and inferential statistics
$224,028/year to $279,400/year + bonus + equity + benefits
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