Director of ML & Data Science — Credit & Risk

LendingClub; San Francisco (CA); Hybrid; USD 210,000 - 245,000; Full time

Benefits offered by this job

Medical, dental and vision plans

401(k) match

Paid parental leave

Job summary

Happen Bank is seeking a Director of Modeling and Data Science in San Francisco to lead ML and statistical models for lending and deposits. You will guide a team of data scientists, set strategic direction, and partner with Risk, Technology, Marketing, and Compliance to drive business decisions while ensuring governance and fairness.

You will apply gradient boosting, deep learning, and ensemble methods, while shaping infrastructure for scalable experimentation and robust documentation.

Qualifications

• 10+ years of experience in machine learning, data science, or credit risk analytics, including 6+ years in people management
• Strong leadership with clear direction, prioritization, and accountability
• Deep technical depth in supervised and unsupervised learning and proficient in Python and ML libraries
• Familiarity with model governance and regulatory frameworks (e.g., SR 11-7, OCC guidance)
• Experience with LLMs or foundation models is a plus

Responsibilities

• Lead end-to-end lifecycle of models across credit, fraud, collections, pricing, and marketing decisioning
• Set modeling roadmap and priorities balancing business impact and regulatory expectations
• Build and mentor a high-performing data science team
• Collaborate with Risk, Engineering, Marketing, and Compliance to align solutions with goals
• Shape ML infrastructure for scalable experimentation and deployment

Skills

Machine learning

Data science

Credit risk analytics

People management

Leadership

Communication

Python

Education

Bachelor's degree in a related field

Master's or PhD in Statistics, Computer Science, Engineering, or Economics

Tools

Scikit-learn

XGBoost

TensorFlow

PyTorch

Job description

Happen Bank is seeking a Director of Modeling and Data Science in San Francisco to lead ML and statistical models for lending and deposits. You will guide a team of data scientists, set strategic direction, and partner with Risk, Technology, Marketing, and Compliance to drive business decisions while ensuring governance and fairness.

You will apply gradient boosting, deep learning, and ensemble methods, while shaping infrastructure for scalable experimentation and robust documentation.