Data Scientist – Technical Leadership
| Company | Meta |
|---|---|
| Location | San Francisco, CA, USA, Los Angeles, CA, USA, Menlo Park, CA, USA, Sunnyvale, CA, USA |
| Salary | $206000 – $281000 |
| Type | Full-Time |
| Degrees | Bachelor’s, Master’s, PhD |
| Experience Level | Senior, Expert or higher |
Requirements
- Bachelor’s degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience
- 5+ years of experience with data querying languages (e.g. SQL), scripting languages (e.g. Python), or statistical/mathematical software (e.g. R, SAS, Matlab)
- 8+ years of work experience leading analytics work in IC capacity, working collaboratively with Engineering and cross-functional partners, and guiding data-influenced product planning, prioritization and strategy development
- Experience working effectively with and leading complex analytics projects across multiple stakeholders and cross-functional teams, including Engineering, PM/TPM, Analytics and Finance
- Experience with predictive modeling, machine learning, and experimentation/causal inference methods
- Experience communicating complex technical topics in a clear, precise, and actionable manner
Responsibilities
- Work with complex data sets to solve challenging problems using analytical and statistical approaches
- Apply technical expertise in quantitative analysis, experimentation, and data mining to develop product strategies
- Identify and measure success through goal setting, forecasting, and monitoring key metrics
- Partner with cross-functional teams to inform and execute product strategy and investment decisions
- Build long-term vision and strategy for programs and products
- Collaborate with executives to define and develop data platforms and instrumentation
- Effectively communicate insights and recommendations to stakeholders
- Define success metrics, forecast changes, and set team goals
- Support developing roadmaps and coordinate analytics efforts across teams
Preferred Qualifications
- Bachelor’s Degree in an analytical or scientific field (e.g. Computer Science, Engineering, Mathematics, Statistics, Operations Research)
- Masters or Ph.D. Degree in a quantitative field
- 10+ years of experience doing complex quantitative analysis in product analytics
- 10+ years of experience communicating the results of analyses to leadership teams to influence the strategy