- Apply expertise in quantitative analysis, data mining, and the presentation of data to see beyond the numbers and understand how Meta users interact with consumer and business products.
- Mine massive amounts of data and perform large-scale data analysis to extract useful business insights.
- Develop data pipelines with automated, machine-learning systems that convert noisy core datasets into powerful signals of user behavior.
- Building models of user behaviors for analysis or to power production systems.
- Partner with Product and Engineering teams to solve problems and identify trends and opportunities.
- Design and implement dashboards and reports that track key business metrics and provide actionable insights.
- Inform, influence, support, and execute product decisions and product launches by effectively communicating results to cross functional groups.
- Work across areas of product operations, exploratory analysis, product leadership, and data infrastructure.
- Requires a Master's degree (foreign degree equivalent accepted) in Computer Science, Engineering, Analytics, Statistics, Mathematics, or a related field.
- Requires completion of a graduate-level course, project or internship involving the following:
- 1. Machine learning techniques
- 2. Working with large data sets and network-based data (TCP or HTTP)
- 3. ETL (Extract, Transform, Load) processes
- 4. Relational database (SQL or PL*SQL)
- 5. Developing in scripting language: PHP, Python, or Perl
- 6. Statistical analysis using R, MATLAB, SPSS, SAS, or Stata
- 7. Large scale data processing infrastructures using distributed systems (Hadoop, Hive, MapReduce, or MPI)
- 8. Quantitative analysis techniques: clustering, regression, pattern recognition, or descriptive and inferential statistics, and
- 9. Communicating and presenting results of data analyses
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