Senior Data Scientist (Marketplace)

About Turtles

Turtles.com is the AI platform for marketplaces. We are growing extremely rapidly and we're now at a $140M+ revenue pace (not GMV) with 30M+ US shoppers across our platforms. We are well-capitalized and profitable. We've grown 4x+ in the last year and believe we can do it again. We're a lean team of 65+ across NYC, Helsinki, and Hong Kong, organized around rapid experimentation, autonomous teams, and no bureaucracy. More than 10,000 new shoppers sign up every day, so every 1% lift is a serious win. We only care about building what's on the critical path for our next 4x, and to become one of the largest companies in online shopping. Turtles isn't for everyone, and that's intentional. If you're energized by solving difficult problems quickly with lots of autonomy, you'll thrive here.

Why join

This is an unusual opportunity. The conventional trade-off is between scale and ownership: established companies provide capital, distribution, and leverage at the cost of autonomy, while startups provide ownership and speed at the cost of resources. This role is a rare combination of both. You'll be sitting directly next to our CEO and VP Engineering every day and have unusual access to core decision making for our scale, with the resources of a company doing nine figures in revenue at your disposal. If you have a good idea in the morning, you can have it live by the end of the day.

About the role

We're looking for an exceptional data scientist to own one of the biggest open problems at Turtles: the economics of our marketplaces. Our marketplaces are real economies with product scheduling, promotions, pricing, and tons of other variables interacting together. Small changes have the potential to swing metrics significantly. You'll be our first dedicated data scientist to work on this problem full time, and you’ll work directly with the CEO and VP Engineering in our NYC office.

What you'll do

- Own our marketplace economy. This will be roughly 80% of the job. How should we schedule products against a fixed pool of daily shoppers? What does a promotion really cost and how much do we make from it? How do we balance scheduling items that are lower margin but higher demand?

- Design experiments and help make sense of the results. Oftentimes something will win and we’re not quite sure why

- Find ways we can improve user acquisition, payment authorization rates, and promotion economics

What we're looking for

- 4+ years of applied analysis on a real consumer business, Ideally in consumer apps, gaming, marketplaces, or performance marketing

- Economic reasoning about systems: pricing, virtual economies, marketplace dynamics

- Healthy skepticism. Sometimes we’ll see results that seem to point in one direction, but the opposite is actually true

- Strong SQL and Python, with experimentation depth beyond running A/B tests

- Exhilarated by results. Analysis you find on Monday should change what the company does that week

Not required, but these are a plus

- Game economy, marketplace pricing, decision science, or applied economics background

- Media buying or UA analytics exposure

- Enough engineering to ship small automations or instrumentation to set up your own experiments (AI-assistance is welcome)

- At least a bachelor’s in a hard-sciences field

Our process A short, focused process designed to respect your time:

- Intro call with our VP Engineering (30 min)

- Working session (90 min): dig into a real marketplace-data problem on real anonymized data

- Visit our office in SoHo and spend 1-2 hours with our CEO and VP Engineering

- Offer within 2-3 days