Data Scientist, Product Analytics
Meta · United States
- Hybrid
- Full-time
- $170,000 / year
- United States
Job highlights
- Shape products used by billions globally.
- Analyze complex, rich data sets.
- Collaborate with diverse cross-functional teams.
- Influence product strategy with data insights.
- Join a world-class analytics community.
About the role
Data Scientist, Product Analytics at Meta
As a Data Scientist at Meta, you will shape the future of people-facing and business-facing products we build across our entire family of applications (Facebook, Instagram, Messenger, WhatsApp, Oculus). By applying your technical skills, analytical mindset, and product intuition to one of the richest data sets in the world, you will help define the experiences we build for billions of people and hundreds of millions of businesses around the world. You will collaborate on a wide array of product and business problems with a wide-range of 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. You will influence product strategy and investment decisions with data, be focused on impact, and collaborate with other teams. By joining Meta, you will become part of a world-class analytics community dedicated to skill development and career growth in analytics and beyond.
Product leadership
You will use data to shape product development, quantify new opportunities, identify upcoming challenges, and ensure the products we build bring value to people, businesses, and Meta. You will help your partner teams prioritize what to build, set goals, and understand their product's ecosystem.
Analytics
You will guide teams using data and insights. You will focus on developing hypotheses and employ a varied toolkit of rigorous analytical approaches, different methodologies, frameworks, and technical approaches to test them.
Communication and influence
You won't simply present data, but tell data-driven stories. You will convince and influence your partners using clear insights and recommendations. You will build credibility through structure and clarity, and be a trusted strategic partner.
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 our products that serve billions of people and hundreds of millions of businesses
- Identify and measure success of product efforts through goal setting, forecasting, and monitoring of key product metrics to understand trends
- Define, understand, and test opportunities and levers to improve the product, and drive roadmaps through your 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
- Bachelor's degree in Mathematics, Statistics, a relevant technical field, or equivalent
- 4+ years of work experience in analytics, data querying languages such as SQL, scripting languages such as Python, and/or statistical mathematical software such as R (minimum of 2 years with a Ph.D.)
- 4+ years of experience solving analytical problems using quantitative approaches, understanding ecosystems, user behaviors & long-term product trends, and leading data-driven projects from definition to execution [including defining metrics, experiment, design, communicating actionable insights]
Preferred Qualifications:
- Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements)
- Experience adhering to and implementing responsible, ethical AI practices (e.g., risk assessment, bias mitigation, quality and accuracy reviews)
- Demonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologies
About Meta:
Meta builds technologies that help people connect, find communities, and grow businesses. When Facebook launched in 2004, it changed the way people connect. Apps like Messenger, Instagram and WhatsApp further empowered billions around the world. Now, Meta is moving beyond 2D screens toward immersive experiences like augmented and virtual reality to help build the next evolution in social technology. People who choose to build their careers by building with us at Meta help shape a future that will take us beyond what digital connection makes possible today—beyond the constraints of screens, the limits of distance, and even the rules of physics.
Meta is proud to be an Equal Employment Opportunity and Affirmative Action employer. We do not discriminate based upon race, religion, color, national origin, sex (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender, gender identity, gender expression, transgender status, sexual stereotypes, age, status as a protected veteran, status as an individual with a disability, or other applicable legally protected characteristics. We also consider qualified applicants with criminal histories, consistent with applicable federal, state and local law. Meta participates in the E-Verify program in certain locations, as required by law. Please note that Meta may leverage artificial intelligence and machine learning technologies in connection with applications for employment.
Meta is committed to providing reasonable accommodations for candidates with disabilities in our recruiting process. If you need any assistance or accommodations due to a disability, please let us know at accommodations-ext@meta.com.
Key skills/competency
- Data Science
- Product Analytics
- SQL
- Python
- R
- Quantitative Analysis
- Experimentation
- Data Mining
- Statistical Analysis
- Machine Learning
Skills & topics
- Data Scientist
- Product Analytics
- Data Science
- Analytics
- SQL
- Python
- R
- Quantitative Analysis
- Experimentation
- Data Mining
- Meta
- Machine Learning
- AI
How to get hired
- Tailor your resume: Highlight data science, analytics, and product intuition skills. Quantify achievements with metrics.
- Showcase technical skills: Emphasize experience with SQL, Python, R, and quantitative analysis.
- Demonstrate product impact: Provide examples of using data to influence product strategy and drive decisions.
- Prepare for interviews: Practice explaining complex data concepts clearly and discussing product challenges.
- Understand Meta's mission: Align your application with Meta's focus on connecting people and building future technologies.
Technical preparation
Behavioral questions
Frequently asked questions
- What are the key responsibilities for a Data Scientist, Product Analytics at Meta?
- As a Data Scientist, Product Analytics at Meta, you will leverage large datasets to solve complex problems, develop product strategies using quantitative analysis and experimentation, define and monitor key product metrics, and partner with cross-functional teams to influence product decisions.
- What technical skills are essential for this Data Scientist role at Meta?
- Essential technical skills include proficiency in data querying languages like SQL, scripting languages such as Python, and statistical software like R. Strong experience in quantitative analysis, experimentation, data mining, and communicating data-driven insights is also crucial.
- What academic background is required for the Data Scientist position at Meta?
- A Bachelor's degree in Computer Science, Computer Engineering, Mathematics, Statistics, or a related technical field is required. Equivalent practical experience is also considered.
- Does Meta value experience with AI tools for Data Scientists?
- Yes, Meta prefers candidates with demonstrated ability to integrate AI tools to optimize workflows and drive measurable impact, experience with ethical AI practices, and ongoing AI skill development.
- How does Meta support career growth for Data Scientists?
- Meta fosters a world-class analytics community dedicated to skill development and career growth, offering opportunities for learning and advancement within analytics and beyond.
- What is the typical career progression for a Data Scientist at Meta?
- While specific paths vary, Data Scientists at Meta typically progress by taking on more complex projects, influencing broader product strategies, potentially leading teams, and specializing in areas like AI/ML or advanced analytics.
- How does Meta approach ethical AI in its Data Science roles?
- Meta emphasizes responsible and ethical AI practices, including risk assessment, bias mitigation, and quality/accuracy reviews, for candidates and employees in Data Science roles.
- What kind of cross-functional collaboration can I expect as a Data Scientist at Meta?
- You can expect to collaborate extensively with Product Managers, Engineers, Researchers, Data Engineers, Marketing, Sales, and Finance teams to drive product strategy and investment decisions.