Staff Data Scientist, Methodologies

About the role

JOIN THE TILT TEAM

At Tilt, we see a side of people that traditional lenders miss. Our mobile-first products and machine learning-powered credit models look beyond credit scores, using over 250 real-time financial signals to recognize real potential. With millions of customers worldwide, we're not just changing how people access financial products — we're creating a new credit system that backs the working, whatever they're working toward.

THE OPPORTUNITY

At Tilt, we’re constantly exploring new ways to understand financial behavior and reduce risk. The work you do in this role will help shape how we use foundational models across our products.

We’re looking for a Staff Data Scientist to join our Methodologies group — a role focused on building and advancing foundational modeling approaches. You’ll explore how deep learning methods such as neural networks, embeddings, and transformers can enhance how we understand financial data and make lending decisions.

This is a great role for someone who’s deeply curious about new modeling techniques and wants to see their ideas make a real difference. You’ll work with a small, experienced team of data scientists and engineers to design and apply deep learning methods to financial data challenges — from credit decisioning to transaction modeling.

You'll also be at the forefront of how data science is practiced in the age of AI agents. Our team builds with agentic tools every day, and we're creating specialized agents that speed up both DS and business workflows.

We’re looking for someone who enjoys learning, experimenting, and collaborating — a person who can connect technical exploration to meaningful business impact. If you’re excited by applying new methodologies in ways that help people access fairer credit, you’ll fit right in.

HOW YOU’LL MAKE AN IMPACT

- Develop and test new modeling approaches using deep learning architectures such as transformers, embeddings, and neural networks.

- Build and refine frameworks that integrate into Tilt’s existing ML pipelines to improve credit modeling and loss prediction.

- Work closely with data scientists, engineers, and product partners to translate complex ideas into practical solutions.

- Experiment with modern representation learning techniques — including pretraining and fine-tuning — on real financial data.

- Share findings and mentor others, helping the team grow its deep learning capability.

- Measure the impact of your models not just by accuracy, but by how they improve outcomes for Tilt’s customers and partners.

- Use agentic development tools (e.g., Claude Code, Codex) to speed up experimentation, feature engineering and model iteration.

- Design and ship specialized agents that support DS and business workflows - these agents turn methodology into leverage across the company.

WHY YOU’RE A GREAT FIT

- Experience with deep learning — neural networks, embeddings, or transformers.