Director, Modeling and Data Science (AI)

Location: Hybrid in San Francisco, United States; in-office Tuesdays, Wednesdays, and Thursdays is essential. Remote placement is not considered. Local hours (PT) are required, with flexibility across time zones when necessary. Relocation to the United States is offered based on actual job level. Travel to hirify.global offices and/or other locations may be required as needed.

Base salary: $210,000–$245,000, plus potential long-term awards and annual bonus.

Company

hirify.global provides focused lending and deposit products through a mobile-first financial services experience designed to help members make financial progress.

What you will do

• Lead the end-to-end lifecycle of machine learning and statistical models across credit, fraud, collections, pricing, and marketing decisioning.
• Set the modeling roadmap and priorities while balancing business impact, regulatory expectations, and team capacity.
• Build, manage, and mentor a team of data scientists and machine learning experts.
• Partner with Credit Strategy, Marketing, Risk, Engineering, Model Risk Management, and Compliance, and explain technical concepts to executives and oversight functions.
• Apply gradient boosting, deep learning, and ensemble modeling to improve model performance.
• Shape ML infrastructure and tooling, identify useful data sources, and ensure documentation, governance, validation, fair lending, and model risk compliance.

Requirements

• 10+ years of experience in machine learning, data science, or credit risk analytics, preferably in consumer lending or financial services, including 6+ years in people management.
• Bachelor’s degree in a related field or equivalent work experience.
• Experience leading teams with clear direction, accountability, and sound prioritization of tradeoffs and risk.
• Strong technical depth in supervised and unsupervised learning, including logistic regression, decision trees, GBMs, and neural networks.
• Proficiency in Python and key ML libraries such as Scikit-learn, XGBoost, TensorFlow, and PyTorch.
• Deep understanding of the model lifecycle from development through monitoring and retraining.
• Familiarity with model governance practices and regulatory frameworks such as SR 11-7 and OCC guidance.
• Understanding of how AI and ML models interact with credit risk decisions, including limitations, failure modes, and regulatory implications.
• Proven record of delivering complex cross-functional projects, managing stakeholder expectations, and bringing partners along as work evolves.

Nice to have

• Hands-on experience developing LLMs and foundation models, including transformer-based sequence models and pre-trained tabular models.
• Master’s or PhD in Statistics, Computer Science, Engineering, Economics, or another quantitative field.

Culture & Benefits

• Hybrid work model with in-person collaboration central to the role.
• Medical, dental, and vision plans for employees and families.
• 401(k) match and health and wellness programs.
• Flexible time off policies for salaried employees.
• Up to 16 weeks of paid parental leave.
• Potential long-term awards and annual performance-based bonus.

Hiring process

• Interviews may be recorded, transcribed, and summarized using AI tools for selected roles and locations.
• Candidates may opt out of recording, transcription, and summarization before scheduled interviews.