Tech Stack

Description

You will build and improve machine learning and GenAI models that power underwriting decisions, taking ownership end-to-end from framing through deployment. You'll work with underwriters, product managers, and engineers to design robust pipelines and ship models that directly impact cyber risk assessment and pricing.

Requirements

• Ph.D. or MS in quantitative field or equivalent experience
• 5+ years full-time experience developing and deploying ML/data solutions in production
• Hands-on experience with supervised and unsupervised learning, model selection, regularization, calibration
• Expertise in statistical analysis, regression, inference, time-series
• Proficiency in Python, ML libraries (scikit-learn, XGBoost, PyTorch/TensorFlow), and SQL

Responsibilities

• Build and advance ML and GenAI models for underwriting decisions
• Drive ML projects end-to-end: problem framing, data exploration, feature engineering, model design, prototyping, evaluation, deployment, monitoring
• Design and implement ML pipelines for preprocessing, training, tuning, and evaluation
• Apply state-of-the-art ML and GenAI techniques (gradient-boosted trees, deep learning, LLMs) to improve underwriting accuracy and automation
• Collaborate with underwriters, product, data, and engineering to integrate models into production