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social media platforms · AI and machine learning

Data Scientist, Analytics (Ranking, AI)

San Francisco Bay Area · New York · Seattle · OnsitePosted 1 month ago
Data Science And StatisticsMid-levelFull Time
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Ranking AI is the central core machine learning org within Meta’s Monetization group, powering Meta’s revenue and business growth by advancing and deploying state-of-the-art Recommendation Systems AI for our Ads stack. We are currently redesigning the large and fragmented Ads model space by developing new modeling architectures, advancing the scale limit through model-hardware co-design, and developing techniques that better leverage anonymized, aggregated data. While there is significant focus on innovation, we pride ourselves in being able to translate research to production with high velocity, delivering on aggressive revenue targets in a predictable fashion.

As a Data Scientist at Meta, 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 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 that 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.

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