Staff Data Scientist - Foundational ML & Agentic Modeling

Tilt; United States; Remote; USD 160,000 - 230,000; Full time

Benefits offered by this job

Virtual-first teamwork

Competitive pay

Complete health coverage

Global onsite events

Leadership exposure

Generous equity

Job summary

Tilt is seeking a Staff Data Scientist to join the Methodologies group. You’ll explore deep learning methods to enhance credit modeling and risk assessment, working with a small, senior team of data scientists and engineers.

You’ll translate complex ideas into practical solutions, experiment with transformers and embeddings, and help shape how foundational models power Tilt’s financial products for diverse customers worldwide.

Qualifications

• Experience with deep learning — neural networks, embeddings, or transformers.
• 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).
• Strength in connecting data science to measurable business outcomes.
• 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.

Responsibilities

• 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.

Skills

Deep learning

Neural networks

Transformers

Embeddings

PyTorch

TensorFlow

Financial services

Tools

PyTorch

TensorFlow

LLMs

Agent frameworks

Job description

Tilt is seeking a Staff Data Scientist to join the Methodologies group. You’ll explore deep learning methods to enhance credit modeling and risk assessment, working with a small, senior team of data scientists and engineers.

You’ll translate complex ideas into practical solutions, experiment with transformers and embeddings, and help shape how foundational models power Tilt’s financial products for diverse customers worldwide.