Data Scientist, Product Analytics

Meta; Lansing (MI); On-site; USD 177,000 - 247,000; Full time

Job summary

Meta in the United States is seeking a Data Scientist focusing on Product Analytics to shape data-driven strategies across our family of apps. You will work with large datasets, collaborate with cross-functional partners, and influence product decisions with rigorous analysis and experimentation.

You will apply statistical methods, build dashboards, and drive measurable impact for billions of users and hundreds of millions of businesses worldwide.

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)

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

Skills

SQL

Python

R

Education

Bachelors in CS/CE or equivalent

Bachelors in Mathematics/Statistics or equivalent

Masters/PhD in quantitative field

Job description

Summary:

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.

Required Skills:

Data Scientist, Product Analytics Responsibilities:

1. Work with large and complex data sets to solve a wide array of challenging problems using different analytical and statistical approaches
2. 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
3. Identify and measure success of product efforts through goal setting, forecasting, and monitoring of key product metrics to understand trends
4. Define, understand, and test opportunities and levers to improve the product, and drive roadmaps through your insights and recommendations
5. Partner with Product, Engineering, and cross-functional teams to inform, influence, support, and execute product strategy and investment decisions

Minimum Qualifications:

Minimum Qualifications:

1. Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience
2. A minimum of 6 years of work experience in analytics (minimum of 4 years with a Ph.D.)
3. Bachelor's degree in Mathematics, Statistics, a relevant technical field, or equivalent practical experience
4. Experience with data querying languages (e.g. SQL), scripting languages (e.g. Python), and/or statistical/mathematical software (e.g. R)

Preferred Qualifications:

Preferred Qualifications:

1. Master's or Ph.D. Degree in a quantitative field
2. Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements)
3. Experience adhering to and implementing responsible, ethical AI practices (e.g., risk assessment, bias mitigation, quality and accuracy reviews)
4. Demonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologies

Public Compensation:

$177,000/year to $247,000/year + bonus + equity + benefits

Industry: Internet

Equal Opportunity:

Meta is proud to be an Equal Employment Opportunity and Affimative 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 [e-mail].