Principal Data Scientist, Product & Pricing Analytics

About the position This is a highly visible role that sits at the intersection of product, data science, and pricing strategy. The Principal Data Scientist, Product & Pricing Analytics will play a key role in ensuring the vibrancy of Udemy's consumer marketplace. In this role, you will work with stakeholders in Product and Marketing to drive data-informed decisions about how we price courses, measure the performance of our econometric pricing algorithms, design and execute experiments, create dashboards to drive revenue maximization efforts, and suggest strategic changes in our pricing and promotions strategy based on insights from user data. Success in this role will require a combination of strong communication and collaboration skills, sharp product sense, a customer-centric mindset, and solid technical data science skills. We are interested in building a diverse, collaborative, and fun environment. Come help us improve lives through learning! Responsibilities • Serve as the embedded product data science partner in a cross-functional team responsible for pricing and product experimentation at Udemy, including PMs, Engineers, and Marketers. • Work with the team to develop a rich program of experimentation to improve the revenue performance of our consumer marketplace including metric creation, experiment design, power analysis, and analysis of experiment results. • Use advanced analytics techniques (e.g., clustering, regression, forecasting) to uncover insights that shape how we serve consumer accounts. • Drive data-informed decision-making within the Product and Pricing teams by equipping PMs, Marketers and Engineers with self-service analytics tools, and conducting ad hoc analyses and causal studies for the team. • Measure price elasticities, average selling prices, and conversion rates in our marketplace, and use those metrics to help brainstorm potential price experiments to drive revenue gains. • Work with Udemy's Pricing & Promotions team to quantify, understand, and prioritize improvements to our pricing system. Collaborate with Data Engineering to improve data pipelines and access. Requirements • Bachelor's degree in a relevant technical field, or equivalent practical experience. • 6+ years of hands-on Data Science or ML Engineering experience (4+ if you have a PhD), with past work in product, customer and/or pricing analytics strongly preferred. • Expert-level SQL and Python skills; experience with Databricks or similar cloud data warehouses. • Broad knowledge of applied statistics, experimental design, and analysis of A/B tests. • Experience working with Github and CI/CD code review processes. • Experience building automated data pipelines using tools like Airflow and dbt. • Exceptional data storytelling and data visualization ability. Nice-to-haves • Experience with Tableau, and a strong eye for visual storytelling and usability, is a big plus. Apply tot his job