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    Meta

    Data Scientist, Product Analytics

    Meta
    Full-time
    USAData ScienceToday

    About this role

    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.ResponsibilitiesWork 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 decisionsQualificationsBachelor'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

    About Meta

    Meta
    Meta

    Meta is a technology company that builds and operates global-scale infrastructure to power innovative digital services and platforms. The company develops data centers that form the foundation of its rapidly scaling infrastructure, delivering services to billions of users worldwide. Meta's engineering teams work across multiple domains—from chip design to building management systems—to optimize efficiency, reliability, and uptime of its compute infrastructure. The company is also investing heavily in AI-powered automation and transformation of operational processes at scale through its Scaled Operations organization.

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