Product Manager, Analytics

Overview

There are millions of e-commerce businesses around the world, and the industry is growing each year, yet achieving profitability has never been harder. Costs are rising, it’s trickier to acquire customers, and it's critical to run with lean teams. As a result, the vast majority of brands guess about things like how to price their products, what discounts to offer, whether to charge for shipping, and what content they should show on the site, leaving 6–10% of potential profit on the table.

Intelligems is a profit growth platform that helps these entrepreneurs succeed by uncovering that profit. Our platform provides e-commerce merchants with a wide range of A/B testing and personalization tools to help them understand their data, run experiments, and price dynamically. We’re taking technology that has previously been available only to the Amazons and Ubers of the world, and making it available to e-commerce stores of any size.

We have excellent traction: we’re working with over 2,000 brands and have access to more than $10B of transaction and shopping session data. As we enter scaling mode, we are looking for highly talented individuals to join us and help us continue to scale efficiently. We have an extremely high-performing team, with a collaborative culture of low-ego + high-IQ people. Our people are our strongest asset, and we hold a very high bar.

We're backed by Stage 2 Ventures, Vinyl Capital, Matchstick Ventures, Techstars, and the founders of companies like Klaviyo and Postscript, and have raised >$11M to date.

We're looking for a product manager to turn Intelligems' data into decisions merchants can actually act on.

This PM leads our Analysis pillar: analytics surfaces, sitewide reporting, post-test metrics, benchmarking, recommendations, and AI-powered interpretation. Intelligems has a data asset most competitors can't replicate, and this PM exists to make that advantage real for merchants who don't have a data team.

This is a high-impact, highly cross-functional role. You'll work closely with data engineering, data science, and the broader product team to define what merchants see, how they interpret it, and how AI closes the distance between data and confident action. The job requires someone who builds for non-analysts, has genuine opinions about where opinionated product experiences matter and where data infrastructure matters more, and can hold their own in technical conversations about how data gets computed and delivered.