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.

About this role

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!

What you'll be doing

• 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, MarTech, 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.

What you'll have

• 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 significant time spent as an embedded product or growth data scientist in a consumer business. Experience supporting top-of-funnel, growth, CRO, SEO, or marketing surfaces is strongly preferred.
• Expert-level SQL and Python; experience with Databricks or a similar cloud data warehouse.
• Deep, applied expertise in experimentation: experimental design, power analysis, A/B and multi-arm testing, variance reduction, sequential testing, and at least working familiarity with quasi-experimental and causal inference methods for when randomization isn't possible.
• Strong product sense - ability to translate ambiguous, open-ended business questions into structured analyses and crisp recommendations, and to push back constructively when the data tells a different story than the team expected.
• Exceptional data storytelling and visualization skills, with a strong eye for narrative and usability. Experience with Tableau is a big plus.
• Experience building automated data pipelines with tools like Airflow and dbt, and working with GitHub and CI/CD code review processes.
• Track record of operating at a Staff level: scoping work across a business area independently, leading cross-functional alignment, defining new metrics and frameworks, and raising the analytical bar for the people around you.
• Strong ownership and ability to work autonomously, while collaborating effectively with teams and colleagues across global time zones.

Posting Date: June 11th, 2026

Application Window: We anticipate the application window will be open until June 24th, 2026. Based on business needs, this opportunity may remain posted beyond or closed before the anticipated application window.

At Udemy, we strive to be transparent around compensation. Actual compensation for this role is based on several factors, including but not limited to job-related skills, qualifications, and experience. In addition to a base salary, this role is also eligible for equity.

Hiring Compensation Range

$156,400-$195,500 USD