Senior Director, Head of Risk Data Science

The Role: Vision & Impact

SoFi is seeking an inspirational and deeply experienced Senior Director to lead and define the strategic direction of our Risk Data Science function. Reporting to the Chief Credit Officer, this executive role will lead the development, deployment, and governance of credit decisioning models - from underwriting and portfolio management to loss mitigation.

The ideal candidate is a hands-on leader and a visionary who can transition the team from traditional modeling to next-generation machine learning platforms, leveraging emerging data sources (e.g., cash flow, alternative bureaus) to significantly improve underwriting performance, reduce losses, and ensure rigorous adherence to Model Risk Management (MRM) standards. This role requires exceptional organizational leadership, an ability to influence executive stakeholders, and proven success in delivering complex models into a regulated production environment.

What You'll Do (Key Responsibilities)

1. Strategic Leadership & Vision:

• Define and Champion Strategy: Develop and articulate the 1-3 year roadmap for Risk Data Science, aligning all priorities with the broader Credit Risk and Business Unit objectives.
• Drive Next-Generation Capabilities: Incorporate industry trends and advanced techniques (NLP, Graph Mining, LLMs, Deep Learning) to solve complex, high-impact risk problems where established principles may not fully apply.
• Talent and Team Development: Lead the current team of high-performing Staff and Senior Data Scientists. Recruit, mentor, and foster talent through deliberate interactions, succession planning, and creating a high-accountability, low-ego culture.

1. Execution & Delivery:

• Underwriting Excellence: Directly oversee the development and deployment of Next Generation Underwriting models designed to increase origination while maintaining loss guardrails.
• Loss Mitigation & Collections: Drive the successful build-out and implementation of new Collection and Entry Rate Models to optimize outreach strategies and reduce losses.
• Loss Forecasting & Compliance: Lead the development of Loss Forecasting and CECL models, ensuring they align with industry practices and meet all regulatory requirements for the firm's balance sheet and reserve calculations.
• Alternative Data Strategy: Spearhead the evaluation and integration of alternative data sources (tri-bureau, LexisNexis, cash flow data) to enhance predictive power across all credit products.

1. Governance, Compliance, and Cross-Functional Influence:

• Model Risk Management (MRM): Act as the primary owner for all models in the portfolio, ensuring robust documentation, monitoring, and successfully navigating the 2nd Line of Defense (2LOD) review and approval process (SR 11-7 familiarity is mandatory).
• Stakeholder Alignment: Interact and negotiate with senior management, executives (CCO, CFO, Product Leads), and external stakeholders to reconcile competing views and drive critical, high-impact business decisions.
• Automation and Efficiency: Lead efforts to automate model monitoring and governance processes (ModelOps) to create scalable and auditable infrastructure.

What You'll Need

• Experience: 12+ years of progressive experience in credit risk, modeling, and data science within a regulated financial institution (FinTech, Bank, or similar), with at least 7 years in a senior leadership/management role (managing managers and/or technical leads).
• Education: Master’s or Ph.D. degree in a quantitative field (Statistics, Computer Science, Engineering, Operations Research, etc.).
• Technical Acumen: Deep expertise in advanced statistical and machine learning modeling techniques (e.g., Gradient Boosting, Deep Learning, Causal Inference).
• Regulatory Knowledge: Detailed working knowledge of model risk management standards (e.g., SR 11-7) and the ability to operate within a highly regulated environment.
• Tools & Platforms: Expert-level proficiency in Python (PySpark, scikit-learn, TensorFlow/PyTorch) and SQL/data warehouse technologies (e.g., Snowflake, Hive). Familiarity with modern MLOps platforms and cloud computing (AWS).
• Communication: Exceptional executive presence and the ability to distill highly complex analytical concepts into clear, concise, and compelling narratives for non-technical leadership.

Why You’ll Love It Here

You will have the autonomy to build the future of risk modeling at a high-growth, innovative financial technology company. Your contributions will directly impact the financial health of millions of members.