Data Scientist – Technical Leadership – Retail Analytics
Company | Meta |
---|---|
Location | Burlingame, CA, USA, New York, NY, USA, Bellevue, WA, USA |
Salary | $206000 – $281000 |
Type | Full-Time |
Degrees | Bachelor’s |
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
- 10+ years of experience with complex quantitative analysis in product analytics