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Responsibilities
- Help build and lead data science teams on projects to deliver world-class products.
- Apply expertise in quantitative analysis, data mining, and the presentation of data to see beyond the numbers and understand how users interact with our products.
- Partner with Product and Engineering teams to solve problems and identify trends and opportunities.
- Manage development of data resources, gather requirements, organize sources, and support product launches and data science projects.
- Analyze data, business intelligence, and statistical results to identify actionable insights, suggest recommendations, and influence the direction of Facebook’s product decisions and product launches by effectively communicating results to cross-functional groups, including Online Ops, Product, and Engineering teams.
- Will leverage data to provide insights about user behavior and to inform business decisions.
- Make business recommendations based on data mining on large, complex data sets and applying concepts in number theory, computational theory, data structures, and algorithms.
- Predict and understand user patterns through analytical and statistical metric analysis.
- Apply quantitative skills in predictive modeling, business intelligence analysis, A/B tests, regression models, and machine learning to gather data insights.
Minimum Qualifications
- Requires a PhD degree (or foreign equivalent) in Applied Physics, Computer Science, Engineering, Sciences, Mathematics, Statistics, Physics, or related field. Requires completion of a university-level course, research project, internship, or thesis in the following:
- Machine learning techniques
- Statistical analysis using R, MATLAB, SPSS, Python, or Perl
- Quantitative analysis techniques: clustering, regression, pattern recognition, or descriptive and inferential statistics
- Communicating and presenting results of data analyses
- Building and analyzing reports and key data sets to empower operations and exploratory analysis
- Translating strategic questions into structured analyses, defining success metrics, and developing reporting
- Building key statistical data sets to empower operational and exploratory analysis and automating analyses
- Assisting in designing hypothesis testing experiments, analyzing data collected, and presenting results
- Conducting ad hoc data analysis based on current team needs
- Mentoring junior team members on defining problems and hypothesis, experimentation, and analytical skills
$289,786/year to $325,270/year + bonus + equity + benefits
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