Senior Data Scientist
Storm2 · San Francisco, CA
قدّم وتابع مع أبلاي إيدجSenior ML Data Scientist | AI-Native FinTech | Onsite, SFWe are partnered with a venture-backed fintech that's reinventing credit underwriting from the ground up.Instead of relying on traditional credit scores, they're building AI-native risk models that leverage transaction data, financial documents, and other structured and unstructured datasets to make lending decisions. Founded by former YC founders and engineers from companies like Square, Facebook, and Box, they've raised capital from top-tier investors and are building one of the most ambitious AI applications in financial services.They're looking for a Senior ML Data Scientist to help shape the future of their credit, fraud, and underwriting platform.What you'll work on:• Building and deploying production ML models across credit risk, underwriting, and fraud• Using embeddings, neural networks, transformers, and LLMs to create richer representations of financial data• Developing underwriting workflows that combine classical ML with modern AI architectures• Designing real-time fraud detection systems using both rules-based and machine learning approaches• Engineering features from structured and unstructured financial datasets• Monitoring model performance, drift, and reliability in production• Partnering with engineering and risk teams to bring models into live decisioning systems• Helping define technical strategy and set the bar for machine learning across the companyWhat they're looking for:• 7+ years of ML, Data Science, Credit Risk, or Fraud experience• Hands-on experience deploying LLMs, embeddings, transformers, or deep learning models into production• Strong Python and SQL skills• Experience with PyTorch, XGBoost, LightGBM, or similar frameworks• Strong fundamentals in statistics, experimentation, anomaly detection, and model evaluation• Experience owning production ML systems end-to-end• Someone who thrives in early-stage environments and enjoys influencing technical direction