Data Scientist, Machine Learning - Product Analytics
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Job Info

As a Machine Learning Data Scientist at Meta, you will have the opportunity to do groundbreaking applied machine learning work that will shape the industry and the future of people-facing and business-facing products we build in Meta Business Suite. This role will be responsible for helping the team develop products such as our business and creator classifiers, unified business graph, as well as recommendation systems for our business tools.By applying your Machine Learning knowledge and 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 diverse set of cross-functional partners across Product, Engineering, Research, Data Engineering, Marketing, Sales, Finance and others. You will use Machine Learning knowledge, 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, data science, machine learning and beyond.About the roleProduct leadership: You will use data to understand the product and business ecosystem, quantify new opportunities, identify upcoming challenges, and shape product development to bring value to people, businesses, and Meta. You will help develop strategy and support leadership in prioritizing what to build and setting goals for execution. Analytics: You will guide product teams using data and insights. You will focus on developing hypotheses and employ a diverse toolkit of rigorous analytical approaches, different methodologies, frameworks, and technical approaches including ML to test them. You will research challenging ML questions to inform experimentation and ML development.Communication and influence: You won't simply present data, but tell data-driven stories. You will convince and influence leaders using clear insights and recommendations. You will build credibility through structure and clarity, and be a trusted strategic partner.

<ul><li>Help define metrics and targets for our product and engineering teams to ensure we accurately identify businesses/creators (and their connections) across Meta platforms.</li><li>Work with business leads to understand new areas where ML can drive value.</li><li>Lead analytics projects end-to-end in partnership with Product, Engineering, and cross-functional teams to inform, influence, support, and execute product strategy and investment decisions.</li><li>Work with large and complex data sets to solve a wide array of challenging problems using different analytical and statistical approaches.</li><li>Apply technical expertise with machine learning, 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.</li><li>Partner with cross-functional engineering and product teams to derive quantitative understanding of Meta's ML infrastructure and ML applications.</li><li>Inform direction and strategic decisions for the future of ML and large scale distributed systems at Meta.</li><li>Identify opportunities and develop solutions in existing large scale distributed systems and ML stack.</li><li>Define, understand, and test opportunities and levers to improve the product through ML models and applications, and drive ML-modeling roadmaps through your insights and recommendations.</li><li>Contribute towards advancing the Data Science discipline at Meta, including but not limited to driving data best practices (e.g. analysis, goaling, experimentation, machine learning), improving analytical processes, scaling knowledge and tools, and mentoring other data scientists.</li></ul>

<ul><li>Currently has, or is in the process of obtaining a Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience. Degree must be completed prior to joining Meta.</li><li>Experience with statistical data analysis such as linear models, multivariate analysis, stochastic models, and sampling methods</li><li>Experience with applying machine learning techniques to big data systems (e.g., Spark and Hadoop) with TB to PB scale datasets</li><li>Experience with data querying languages (e.g. SQL), scripting languages (e.g. Python), and/or statistical/mathematical software (e.g. R)</li></ul>

<ul><li>Masters or PhD in a quantitative field</li><li>Strong research record demonstrated through publications</li><li>Knowledge of one or more of advanced ML techniques such as Classification, Clustering, Embedding, Deep Neural Network, Prediction, Recommender Systems, Optimization, and Graph ML</li></ul>

Facebook's mission is to give people the power to build community and bring the world closer together. Through our family of apps and services, we're building a different kind of company that connects billions of people around the world, gives them ways to share what matters most to them, and helps bring people closer together. Whether we're creating new products or helping a small business expand its reach, people at Facebook are builders at heart. Our global teams are constantly iterating, solving problems, and working together to empower people around the world to build community and connect in meaningful ways. Together, we can help people build stronger communities - we're just getting started.

Facebook is proud to be an Equal 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.Facebook 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@fb.com.