Head of Risk, Decision Science – Portfolio Strategy

Role Overview

• Own the performance and outcome of all deployed statistical and machine learning models, ensuring a seamless translation from data science output to effective underwriting decisions and measurable portfolio results.
• Establish rigorous monitoring and feedback loops between model outputs and real-world credit outcomes.
• Drive use of alternative data (transaction-level signals, partner platform data, behavioral indicators) to improve model accuracy and expand approval rates.
• Own model risk governance including model documentation, validation processes, and ongoing performance standards across all deployed models.
• Direct the end-to-end credit strategy, translating risk models and data insights into a cohesive set of underwriting policies, approval strategies, and pricing frameworks to deliver target loss and growth performance.
• Own approval logic, pre-qualification strategies, and credit limit frameworks that balance growth targets, merchant experience, and credit loss thresholds.
• Set minimum acceptance criteria aligned with Pipe's risk appetite while optimizing approval rates, customer lifetime value, and capital facility performance.
• Design and implement pricing frameworks to ensure appropriate loss coverage and positive borrower selection.
• Own portfolio performance reporting and forward-looking risk adjustments across all credit products.
• Build early-warning systems and structured decision processes that enable fast, disciplined credit strategy adjustments.
• Ensure portfolio resilience across economic cycles through proactive monitoring and timely action.
• Act as the primary owner of our data quality roadmap, identifying discrepancies and driving technical solutions to resolve them.
• Proactively identify and acquire net-new data sources (internal or third-party) to solve for missing signals and improve model accuracy.
• Translate business requirements into clear data engineering and infrastructure specs, ensuring we have the right inputs for reliable, scalable risk decisioning.
• Work closely with Risk Operations to ensure credit strategy is implemented reliably in production systems and iterated quickly based on portfolio results.
• Partner with Capital Markets and Finance on loss forecasting, reserve setting, and risk appetite frameworks; manage credit policy to maintain compliance with facility covenants and triggers.
• Collaborate with Product and Engineering to build scalable decisioning infrastructure that enables rapid strategy iteration.
• Lead a team of seven risk specialists responsible for model building, credit strategy translation, and portfolio monitoring.
• Create clarity, momentum, and accountability while maintaining a sustainable pace of execution.
• Build a culture of analytical rigor, pragmatism, and bias for action.

Requirements

• 8+ years in credit risk, with meaningful experience at a fintech, marketplace lender, or bank with consumer or SMB lending products.
• Deep expertise in credit strategy across MCA or unsecured loan products.
• Hands-on background in machine learning and statistical modeling for credit decisioning (gradient boosting, logistic regression, survival models, etc.).
• Proven ability to translate model outputs into underwriting policies, approval logic, and pricing frameworks that drive portfolio results.
• Track record of improving portfolio performance with speed and accountability in early-stage or high-growth environments.
• Experience building monitoring frameworks, early-warning systems, and feedback loops between strategy and outcomes.
• Strong cross-functional instincts: able to work effectively with Risk Ops, Engineering, Product, Capital Markets, and Finance.
• A "first-principles" operator mindset: you treat data quality issues as critical production incidents you actively debug rather than delegate.
• Deep comfort in the stack: you are fluent in Python/SQL and willing to dive into raw data logs to diagnose anomalies.
• Strategic data ownership: demonstrated success not just in optimizing existing models, but in sourcing and integrating the net-new data required to unlock better credit performance.

Tech Stack

• Python
• SQL

Benefits

• The best equipment to help you do your job.
• Flexible vacation and work hours. We believe in a healthy work-life balance (really!)
• Excellent health, dental, and vision insurance.
• Generous parental leave for anyone who is growing their family, regardless of gender.
• Great colleagues! We value a culture of authenticity, humility, and excellence. We want you to make a mark on our culture.