Data Scientist

About your skills

You're a data scientist who lives at the intersection of product, experimentation, and storytelling. You know that a great A/B test is only the beginning — the harder, more interesting work is figuring out why a treatment moved (or didn't move) the metric, what it tells you about your customers, and what the team should try next. You're fluent in SQL, Python, and modern experimentation practice, and you have a strong product instinct that lets you turn ambiguous business questions into well‑framed analyses.

You partner naturally with PMs, designers, engineers, and marketers; you’re as comfortable shaping a roadmap conversation as you are debugging a tracking pipeline. You care about scaling your impact through better tooling, sharper metrics, and analytics that other people can actually use without you in the room.

This is a highly visible role on Udemy’s Consumer Product Analytics team, embedded with the product, design, and engineering teams who own the top of our consumer funnel — from how learners discover Udemy, through landing pages and search, into the purchase path and checkout. The Staff Data Scientist, Product Analytics will be the senior analytics partner for a portfolio of discovery and conversion squads, including teams working on conversion rate optimization, SEO, marketing technology, and our homepage and landing experiences.

You will help these teams run a high‑velocity experimentation program, define the metrics and dashboards they make decisions with, and use causal and behavioral analysis to surface the next big opportunities in the funnel. Your insights will directly shape how millions of learners around the world experience Udemy’s consumer marketplace and subscription products.

Success in this role will require a combination of strong communication and collaboration skills, sharp product sense, deep experimentation rigor, and a customer‑centric mindset. We are interested in building a diverse, collaborative, and fun environment. Come help us improve lives through learning!

• Serve as the embedded product data science partner for a cross‑functional area focused on discovery and conversion — including PMs, designers, engineers, and marketers across CRO, SEO, Mar Tech, and homepage/landing surfaces.
• Drive a high‑throughput experimentation program end‑to‑end: hypothesis development, metric and guardrail design, power analysis, test design (including geo, switchback, and CUPED‑style variance reduction where appropriate), readout, and meta‑analysis across portfolios of tests.
• Own the analytical strategy for your business area — define the KPIs, secondary metrics, and segmentations that the team uses to evaluate the funnel, and continuously raise the bar on how rigorously decisions get made.
• Build and maintain the dashboards and self‑service analytics that PMs, marketers, and leadership rely on for acquisition, conversion, and consumer subscriptions performance; ensure they are trusted, well‑documented, and resilient to upstream data changes.
• Use advanced analytics techniques (causal inference, regression, clustering, forecasting, segmentation) to characterize learner behavior across the funnel and uncover non‑obvious opportunities; conduct ad‑hoc analyses and causal studies for the team’s most pressing open questions.
• Translate findings into clear, actionable narratives for senior product and business leaders — written readouts, presentations, and recommendations that move roadmaps.
• Partner with Data Engineering and Analytics Engineering to improve event instrumentation, data models, and pipelines that your business area depends on.
• Set the standard for analytical rigor on the team: review experiment designs and analyses from peers, mentor more junior data scientists, and contribute to shared frameworks, tooling, and best practices.
• Shape the longer‑term analytics roadmap and OKRs for your area in partnership with product and DS leadership.

• Bachelor’s degree in a relevant technical field, or equivalent practical experience. Advanced degree a plus.
• 6+ years of hands‑on Data Science experience (4+ with a PhD), with…