Lead Data Scientist, Methodologies

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.

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. 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.