Who you are
Hands-on experience building and training deep learning models
Comfort working with modern ML frameworks (PyTorch, TensorFlow, or similar)
Experience applying ML to real-world problems, ideally in financial services (credit, lending, payments, or banking)
Experience taking a project from an open question to a measurable business outcome
Clear, thoughtful communication — you can explain technical ideas in ways others can engage with
Bonus: hands-on experience building with LLMs or agent frameworks, or excitement to learn. You see agents as a way to multiply what a small, senior team can do
Don’t meet every qualification? We care about potential over your past. If you're bringing ambition and drive to what we're building, we want to hear from you
What the job involves
At Tilt, we're constantly exploring new ways to understand financial behavior and reduce risk. The work you do in this role will go directly into the foundational models we're building for our products
We're looking for a Senior Data Scientist to join our Methodologies group — a role focused on building and advancing foundational modeling approaches. You'll build and test deep learning methods such as transformers to improve 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, taking projects from first idea to working model on financial data challenges — from credit decisioning to customer behavior!
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 you'll use them in your own work and help build the 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
Build, train and evaluate deep learning models on Tilt's financial data
Ship models and model components that plug into Tilt's existing ML pipelines to improve credit modeling and loss prediction
Own your projects end to end, from hypothesis to a model in use, with general direction from the team's leads
Work closely with data scientists, engineers, and product partners to turn your results into practical solutions
Run representation learning experiments — including pretraining and fine-tuning — on real financial data, with a clear design up front and an honest read on what worked
Share findings and help peers pick up new deep learning methods
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
Build and improve specialized agents that support DS workflows
Benefits
Virtual-first teamwork: Great work happens anywhere. We're collaborating across 14 countries, 12 time zones
Full health coverage: Find flexible plans at every premium level and substantial subsidies that stand up to global standards