Data Scientist, Product Analytics
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Key skills for this role
About the Role
Meta is seeking a Data Scientist to shape product experiences across Facebook, Instagram, Messenger, WhatsApp, and Oculus. You will apply quantitative analysis, experimentation, and data mining to influence product strategy and investment decisions.
Key Skills for This Role
Responsibilities
- Work with large and complex data sets to solve a wide array of challenging problems using different analytical and statistical approaches
- Apply technical expertise with quantitative analysis, experimentation, data mining, and the presentation of data to develop strategies for products
- Identify and measure success of product efforts through goal setting, forecasting, and monitoring of key product metrics
- Define, understand, and test opportunities and levers to improve the product, and drive roadmaps through insights and recommendations
- Partner with Product, Engineering, and cross functional teams to inform, influence, support, and execute product strategy and investment decisions
Requirements
- Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience
- Minimum of 6 years of work experience in analytics (minimum of 4 years with a Ph.D.)
- Experience with data querying languages (e.g. SQL), scripting languages (e.g. Python), and/or statistical/mathematical software (e.g. R)
- Master's or Ph.D. Degree in a quantitative field (preferred)
- Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (preferred)
- Experience adhering to and implementing responsible, ethical AI practices (preferred)
- Demonstrated ongoing AI skill development (preferred)
Full Job Posting
Role Overview
- As a Data Scientist at Meta, you will shape the future of people facing and business facing products across Facebook, Instagram, Messenger, WhatsApp, Oculus.
- You will collaborate with cross functional partners across Product, Engineering, Research, Data Engineering, Marketing, Sales, Finance and others.
- You will use data and analysis to identify and solve product development's biggest challenges and influence product strategy.
Data Scientist, Product Analytics Responsibilities
- Work with large and complex data sets to solve a wide array of challenging problems using different analytical and statistical approaches.
- Apply technical expertise with quantitative analysis, experimentation, data mining, and the presentation of data to develop strategies for products.
- Identify and measure success of product efforts through goal setting, forecasting, and monitoring of key product metrics.
- Define, understand, and test opportunities and levers to improve the product, and drive roadmaps through insights and recommendations.
- Partner with Product, Engineering, and cross functional teams to inform, influence, support, and execute product strategy and investment decisions.
Minimum Qualifications
- Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience.
- A minimum of 6 years of work experience in analytics (minimum of 4 years with a Ph.D.).
- Bachelor's degree in Mathematics, Statistics, a relevant technical field, or equivalent practical experience.
- Experience with data querying languages (e.g. SQL), scripting languages (e.g. Python), and/or statistical/mathematical software (e.g. R).
Preferred Qualifications
- Master's or Ph.D. Degree in a quantitative field.
- Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact.
- Experience adhering to and implementing responsible, ethical AI practices.
- Demonstrated ongoing AI skill development and staying current with emerging AI technologies.
Compensation
- $177,000/year to $247,000/year + bonus + equity + benefits.
- Individual compensation is determined by skills, qualifications, experience, and location.
About Meta
- Meta builds technologies that help people connect, find communities, and grow businesses.
- Meta is moving beyond 2D screens toward immersive experiences like augmented and virtual reality.
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