Head of Risk, Decision Science & Portfolio Strategy

Pipe Technologies · Remote, United States · Remote

Posted 7/8/2026 · last confirmed live 8/26/2026

About Pipe Pipe builds embedded capital for small businesses everywhere: credit products delivered inside the software platforms SMBs already use to run their businesses (think vertical SaaS, payments platforms, and marketplaces). We're growing fast, with 250% ARR growth year over year, new partnerships with some of the world's biggest brands, and expansion into new global markets. How it works : merchants get an offer on the platform, understand it in seconds, accept it in four clicks, and pay automatically as they earn. Behind that simplicity sits real credit risk, partner SDKs and APIs, money movement infrastructure, and capital markets infrastructure. We're a remote-first team that ships fast, has high trust of our platform partners like Uber Eats, holds each other to a high bar, and leaves egos at the door. The Role We're looking for a Head of Risk, Decision Science & Portfolio Strategy leader to take end-to-end ownership of Pipe's credit strategy and risk outcomes. This is a senior, hands-on leadership role. You won't just oversee strategy; you own the data chain; from raw, messy ingestion to final credit decisioning. You are the architect of our risk infrastructure, responsible for identifying data gaps, driving the requirements to acquire net-new signals, and ensuring absolute data integrity. You create clarity and momentum in fast-moving environments by rolling up your sleeves to troubleshoot issues, refine models, and build the systems that connect technical outputs to real-world business results. The right person combines analytical rigor with pragmatism, urgency with judgment, and the grit to deliver meaningful results fast. You're comfortable rolling up your sleeves, working through imperfect data and systems, and driving accountability without burning out the team. You create clarity and momentum in fast-moving environments. Success in the first three months will be measured by concrete process and policy improvements expected to drive portfolio performance, along with high trust earned with internal and external stakeholders. Over time, you'll help scale Pipe's risk infrastructure and modeling capabilities. But the immediate focus is clear: operate the credit strategy with discipline, speed, and ownership of outcomes. What you’ll do Model Deployment & Performance 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.  Credit Strategy & Underwriting 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. Portfolio Monitoring & Risk Management 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. Data Integrity & Acquisition Strategy 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. Cross-Functional Execution 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. Team Leadership 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. What we’re looking for Required 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. Preferred Experience with embedded finance, B2B2C distribution models, or platform-based lending. Familiarity with alternative data sources (bank transaction data, payment processing data, SaaS MRR) for underwriting. Background in credit for underserved or thin-file borrowers. Proficiency in Python, SQL, or R for hands-on analysis and model work. Compensation and Benefits We are a fully remote company and we believe in taking care of our employees. As a Pipe employee, you'll receive: 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. The annual US base salary range for this role is $270,000 - $300,000. This salary range may be inclusive of several career levels at Pipe and will be narrowed during the interview process based on a number of factors, including the candidate's experience, qualifications, and location.

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