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Staff Applied Scientist, Personalization

OnePay

🌍 North America 🏠 Remote ⏱ Part-time 💼 Senior 🗓 2 weeks ago

ABOUT ONEPAY

OnePay is the consumer fintech trusted by millions of Americans to make money better.

Our financial system is broken. High fees, low rates, and too few ways to actually grow your money. We’re fixing it. And we’re moving fast.

We’re an all-in-one financial services platform that brings together banking, high-yield savings, credit cards, point-of-sale lending, investing, and crypto in one place. We also partner with employers, HCM providers, gig platforms, and others to deliver embedded financial services to millions of employees and frontline workers.

We’re backed by Walmart, the world’s largest retailer, and Ribbit Capital, one of fintech’s most respected investors, giving us rare scale, distribution, and the opportunity to build something truly category-defining.

But what really sets OnePay apart is how we move. Our customers don’t have time to wait… and neither do we. This place moves fast, and we’re looking for people who are:

- Ready to run

- Hungry and driven by urgency

- Exceptional at what they do, with low ego

- Comfortable operating in motion

THE ROLE

As an Applied Scientist at OnePay, you’ll be at the forefront of our AI and Machine Learning innovation! You will:

- Design and deploy machine learning, deep learning, and LLM models that will shape our customer experience, drive business growth, and improve operational efficiency while collaborating closely with product, engineering, and analytics teams.

- Develop personalization and recommendation systems that deliver dynamic, user-centric experiences across our product offerings.

- Design and optimize search and retrieval systems to improve discoverability, relevance, and user satisfaction.

YOU BRING

- 7+ years of experience building and productionizing ML/AI models that deliver measurable business impact.

- Experience building and productionizing LLM-powered applications, agentic systems, and traditional ML (ranking, recommendations, personalization).

- A strong t...

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