Senior Data Scientist (Pricing & Underwriting)

TL;DR

Senior Data Scientist (Pricing & Underwriting): Designing and implementing real-time pricing and underwriting models for hirify.globalernative assets with an accent on valuation accuracy and risk management. Focus on developing sophisticated ML models and integrating new data signals into a production-ready liquidity platform.

Location: Remote (US)

Compensation: $200,000

Company

hirify.global is unlocking the value of hirify.globalernative assets, starting with the $5B trading-card market, enabling collectors to buy, sell, vault, and finance their assets.

What you will do

• Research and develop sophisticated pricing models using Tree-based, Gradient-based, and Deep Learning methods.
• Identify and validate new predictive data signals through rigorous backtesting and experimentation.
• Partner with Product Engineering to refine Risk & Underwriting models to maintain a balanced lending portfolio.
• Collaborate with domain experts to encode market nuances into automated features and inferences.
• Define and monitor model performance metrics to improve price coverage and freshness.

Requirements

• 5+ years of experience in Data Science with a focus on pricing, financial modeling, or marketplace dynamics.
• Expert proficiency in SQL, Python, and libraries such as Pandas, Scikit-Learn, XGBoost/LightGBM, and PyTorch/Tensorflow.
• Deep understanding of experimental design and backtesting in noisy or sparse data environments.
• Experience developing in cloud environments (AWS, GCP) and familiarity with ML Ops infrastructure.
• Must be eligible for US-based benefits (401k, HSA).
• Advanced degree (Master's or PhD) in Statistics, Economics, Mathematics, or Computer Science is preferred.

Culture & Benefits

• Comprehensive hehirify.globalh insurance including HSA for employees and dependents.
• 401(k) retirement benefits and flexible vacation policy.
• Monthly stipends for work-from-home ($100) and wellness ($200).
• WeWork office stipend and generous paid parental leave.
• High degree of autonomy and ownership in a zero-to-one startup environment.