About Pinterest: Millions of people around the world come to our platform to find creative ideas, dream about new possibilities and plan for memories that will last a lifetime. At Pinterest, we're on a mission to bring everyone the inspiration to create a life they love, and that starts with the people behind the product. Discover a career where you ignite innovation for millions, transform passion into growth opportunities, celebrate each other's unique experiences and embrace theflexibility to do your best work. Creating a career you love? It's Possible. Pinterest is the world's leading visual search and discovery platform, serving over 500 million monthly active users globally on their journey from inspiration to action. At Pinterest, Shopping is a strategic initiative that aims to help Pinners take action by surfacing the most relevant content, at the right time, in the best user-friendly way. We do this through a combination of innovative product interfaces, and sophisticated recommendation systems. We are looking for a Staff Data Scientist with experience in machine learning and causal inference to help advance Shopping at Pinterest. In your role you will develop methods and models to explain why certain content is being promoted (or not) for a Pinner. You will work in a highly collaborative and cross-functional environment, and be responsible for partnering with Product Managers and Machine Learning Engineers. You are expected to develop a deep understanding of our recommendation system, and generate insights and robust methodologies to answer the "why". The results of your work will influence our development teams, and drive product innovation. What you'll do Take an ecosystem view of our homefeed recommendations and understand the impact of components (modules, local navigation, ideas boards etc) individually and collectively. Formulate strong product hypotheses and drive horizontal alignment across several cross-functional teams. Develop robust frameworks, combining online and offline methods, to comprehensively understand the ecosystem value of product decisions. Help teams see the global maximum while enabling local optimizations of features. Bring scientific rigor and statistical methods to the challenges of product creation, development and improvement with an appreciation for the behaviors of our Pinners. Help drive tradeoff decisions, and balance short-term vs long-term impact. Work cross-functionally to build relationships. This is a horizontal role and requires close collaboration with multiple stakeholders on Product and Engineering. Excellent communications skills are just as critical as technical skills. Relentlessly focus on impact, whether through influencing product strategy, advancing our north star metrics, or improving a critical process. Mentor and up-level junior data scientists on the team. What we're looking for 7+ years of experience analyzing data in a fast-paced, data-driven environment with proven ability to apply scientific methods to solve real-world problems on web-scale data Strong interest and experience in recommendation ecosystem health and causal inference Strong quantitative programming (Python/R) and data manipulation skills (SQL/Spark) Ability to work independently and drive your own projects Excellent written and communication skills, and able to explain learnings to both technical and non-technical partners A team player eager to partner with cross-functional partners to quickly turn insights into actions In-Office Requirement Statement: We let the type of work you do guide the collaboration style. That means we're not always working in an office, but we continue to gather for key moments of collaboration and connection. Relocation Statement: This position is not eligible for relocation assistance. Visit our PinFlex page to learn more about our working model.
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