• 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.

• Mitigar el riesgo operativo • Establecer el control metodológico • Desplegar rituales de alto rendimiento basados en datos • Diseñar, estructurar e implementar marcos sólidos de gobierno de procesos a nivel corporativo • Definir e iterar matrices de control y marcos normativos

• Own and optimize margin calculations across all supported modes, including Isolated, Cross, and Portfolio Margin. • Develop and refine risk parameters (maintenance margin, initial margin, and haircut models) to ensure the exchange is robust against extreme market volatility. • Conduct stress testing and back-testing on margin models to ensure they withstand "black swan" events. • Perform post-mortem analysis on trader liquidations to identify patterns of failure. • Investigate cases of negative equity (socialized losses/ADL) to determine why margin was insufficient and recommend adjustments to the insurance fund or liquidation engine logic. • Partner with the engineering team to design and build real-time Risk Dashboards that monitor exchange-wide health, leverage ratios, and margin utilization. • Translate complex risk requirements into technical specifications for the development of automated risk-mitigation tools. • Collaborate with the Customer Experience (CX) team to investigate trader complaints regarding high slippage or liquidity constraints. • Analyze order book depth and execution quality to understand how liquidity gaps contribute to liquidation cascades.

Role Description We are looking for a highly analytical and technically-minded Risk Manager to join our Risk & Clearing team at Delta Exchange. You will be the primary owner of our exchange’s margin ecosystem, ensuring that our collateral requirements are balanced between capital efficiency for traders and systemic safety for the platform. The ideal candidate has a deep understanding of derivatives market structures, a data-driven approach to liquidation analysis, and the ability to bridge the gap between complex financial risk and product development. Core Responsibilities - Margin Methodology & Oversight - Own and optimize margin calculations across all supported modes, including Isolated, Cross, and Portfolio Margin. - Develop and refine risk parameters (maintenance margin, initial margin, and haircut models) to ensure the exchange is robust against extreme market volatility. - Conduct stress testing and back-testing on margin models to ensure they withstand "black swan" events. - Liquidation & Negative Equity Analysis - Perform post-mortem analysis on trader liquidations to identify patterns of failure. - Investigate cases of negative equity (socialized losses/ADL) to determine why margin was insufficient and recommend adjustments to the insurance fund or liquidation engine logic. - Product & Technical Collaboration - Tech Liaison: Partner with the engineering team to design and build real-time Risk Dashboards that monitor exchange-wide health, leverage ratios, and margin utilization. - Translate complex risk requirements into technical specifications for the development of automated risk-mitigation tools. - Trader Experience & Market Microstructure - Collaborate with the Customer Experience (CX) team to investigate trader complaints regarding high slippage or liquidity constraints. - Analyze order book depth and execution quality to understand how liquidity gaps contribute to liquidation cascades. Qualifications - Experience: 3–5 years in Risk Management, Quantitative Analysis, or Operations within a Crypto Exchange, FinTech, or Traditional Derivatives Clearinghouse (CCP). - Deep Domain Knowledge: Strong grasp of perpetual swaps, futures, and the mechanics of auto-deleveraging (ADL). - Technical Proficiency: Ability to work with SQL for data extraction and Python/R for quantitative modeling. Experience with BI tools (Tableau, Grafana, or Looker) is a plus. - Problem Solving: A "detective" mindset—you enjoy digging into trade logs to find out exactly why a liquidation went wrong. - Communication: Ability to explain complex margin mechanics to non-technical stakeholders and customers. Benefits - Collaborative remote work environment that allows you to have a work life balance. - Growth framework that drives fast, continuous improvement. - Opportunity to learn and collaborate with the leadership team. - Exciting team offsites and employee engagement activities.