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Data Scientist, Product Analytics

Job in Dallas, Dallas County, Texas, 75201, USA
Listing for: Devconnectplatform
Full Time position
Listed on 2026-11-01
Job specializations:
  • IT/Tech
    Data Scientist, Data Analyst, AI Engineer (Applied/Software)
Salary/Wage Range or Industry Benchmark: 120000 - 180000 USD Yearly USD 120000.00 180000.00 YEAR
Job Description & How to Apply Below
# Data Scientist, Product Analytics Meta Salary  not stated

Full-time remote
· midUSAsqlpython

Listed via Jobicy
· posted 15 Oct 2026. The application happens there, not on Dev Connect.

Apply on Jobicy## Description 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, Whats App, 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.

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

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) Master's or Ph.D. Degree in a quantitative field  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
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