Simular

Where multiple locations are listed for this role, the position may be based in any of those locations, with priority determined according to the order of listing. Agents generate an unusual amount of data: every run, every step, every recovery from failure. Buried in that data is the answer to which agent behaviors actually work and where users get stuck. Not enough of it is being read today. You'll own analysis that shapes what we build next, working directly with product and engineering. What you'll do Build and maintain dashboards that track product health: activation, retention, task success, and agent reliability Analyze agent run data to find where tasks fail, stall, or need human rescue Answer product questions with data, and be honest when the data can't answer them Help define and instrument the events and metrics we should be tracking in the first place Support experiment design and read out results without overclaiming Turn analysis into recommendations, with a clear view of what you'd do next Make your work reproducible so others can build on it You might be a fit if You're pursuing a Bachelor's or Master's degree in Statistics, Computer Science, Economics, Engineering, or a related field, or equivalent experience You're solid with SQL and comfortable in Python or R for analysis You've built a dashboard or analysis someone else actually used You understand the basics of experimentation and are appropriately skeptical of noisy results You can explain a finding to someone who won't read the notebook You're curious about the product, not just the numbers Bonus: experience with product analytics tools, dbt, or working with event data at scale