About the company: Well-funded NYC AI startup building a behavior model that predicts how online shoppers decide. Its AI runs live experiments on eCommerce stores to lift conversion. Small team, direct work with the founders, 4 days/week in Midtown.

Why join

Every day, millions of people decide whether to buy something online, and the reasons behind those decisions are still mostly guesswork. The company is working to quantify human psychology: to build an embedding model for human behavior that understands how people react to a page, a price, or a single sentence, and can predict what will work before anyone runs a test.

Every experiment the AI runs on a live store teaches that model something about how people decide. The goal is for any company to be able to ask, "I'm selling product X to audience Y, how do I optimize for Z?" and get an answer it can trust.

The company is early and well funded. The people who join now will pick the tools, design the models, and help choose who joins next.

Applied Scientist, Behavior Modeling

Every day the company's script records tens of millions of actions from people visiting the websites it works with: what they look at, where they hesitate, what they click, and when they leave. You'll turn that into the first version of the behavior model. The goal is a model that predicts how people are likely to interact with a website, and what the site should and shouldn't do for them.

The work starts with online stores, by spotting which visitors are close to buying and which groups need to see a different version of the page. Researchers have published a lot about learning from user behavior with sequence models and embeddings, so you won't start from a blank page. Your job is to know that work well, pick what fits the data, get it working here, and keep up as the field moves.

You'd be the first person working on this full time, so a lot rests on your shoulders.

What you'll work on

• The behavior model. Build the first model that turns raw session events into embeddings of how a visitor behaves. Pre-training a transformer on event sequences is a likely start, but you'll make the call. The hard part is that most sessions are short and anonymous, and most visitors never come back.
• Buying intent and audiences. Use the model to spot buying intent during a session and to group visitors into audiences, so the AI can show each audience the page version that works for it. A first version goes on live stores as soon as it works, then improves from there.
• New research. When a paper comes out that could help, you'll read it, try it on the data, and decide whether to use it. If you learn something worth publishing, publish it.

Stack: mostly Python, with event data in ClickHouse and services on AWS. You'll report directly to the CTO and work every day with the engineers who build on your model and the client team who explain to stores why the AI showed their shoppers a different page.

You'll love this job if

• You read papers and get impatient until you've tried the idea on real data.
• You'd rather adapt a proven method and see it work in three weeks than spend a year inventing a new one.
• You want a big, open problem that's yours to figure out, with engineers and the founders working right next to you.
• You're fine working with noisy event logs and writing your own SQL to get at them.
• You were the person in your lab others came to when they needed a hard idea made simple.
• You want to help build a model that understands how people make decisions, and be there for the first version of it.

What you bring

• A PhD or equivalent research experience in a quantitative field. People from physics, math, computational biology, and neuroscience often fit well, especially if you've modeled behavior or sequences.
• You've trained a model on messy, real-world sequence or time-series data yourself, and you've shown whether it worked.
• You know the recent work on learning from sequences (transformers, self-supervised pre-training, embeddings) well enough to choose between approaches and explain why.
• You write solid Python and can pull your own data with SQL.
• You've given talks or written for people outside your field, and they followed.
• Bonus: experience with recommendation systems or user behavior data, large event datasets, or eCommerce.

Values

• Curiosity and excellence: Asking questions is the job. The team pushes on each other's ideas, and a failed experiment teaches as much as a winning one.
• Whatever it takes: If something needs doing, whoever can do it does it, whatever their title.
• Ownership: Shipping something is where the work starts. You follow it all the way to the result.
• Agility: Most ideas go from whiteboard to working prototype in two or three days.
• Enjoy the ride: Building something new comes with rough weeks. The team gets through them together.

What's offered

• Base salary $165K - $220K plus meaningful equity
• Medical, dental, and vision for you and your family
• Unlimited PTO
• Tax-free commuter and parking benefits
• Office-first culture (4 days/week) in Midtown Manhattan
• Work directly with the founding team
• Free One Medical membership
• 401k