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SoFi

Senior Director, Head of Risk Data Science

Reposted Yesterday
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Hybrid
8 Locations
Senior level
Easy Apply
Hybrid
8 Locations
Senior level
The role involves leading Risk Data Science, developing credit decisioning models, and ensuring compliance with model risk management in a regulated environment, focusing on next-gen machine learning techniques and alternative data integration.
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Who we are:

Shape a brighter financial future with us.

Together with our members, we’re changing the way people think about and interact with personal finance.

We’re a next-generation financial services company and national bank using innovative, mobile-first technology to help our millions of members reach their goals. The industry is going through an unprecedented transformation, and we’re at the forefront. We’re proud to come to work every day knowing that what we do has a direct impact on people’s lives, with our core values guiding us every step of the way. Join us to invest in yourself, your career, and the financial world.

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.

Compensation and Benefits
The base pay range for this role is listed below. Final base pay offer will be determined based on individual factors such as the candidate’s experience, skills, and location. 
 
To view all of our comprehensive and competitive benefits, visit our Benefits at SoFi page!
SoFi provides equal employment opportunities (EEO) to all employees and applicants for employment without regard to race, color, religion (including religious dress and grooming practices), sex (including pregnancy, childbirth and related medical conditions, breastfeeding, and conditions related to breastfeeding), gender, gender identity, gender expression, national origin, ancestry, age (40 or over), physical or medical disability, medical condition, marital status, registered domestic partner status, sexual orientation, genetic information, military and/or veteran status, or any other basis prohibited by applicable state or federal law.The Company hires the best qualified candidate for the job, without regard to protected characteristics.Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.New York applicants: Notice of Employee RightsSoFi is committed to an inclusive culture. As part of this commitment, SoFi offers reasonable accommodations to candidates with physical or mental disabilities. If you need accommodations to participate in the job application or interview process, please let your recruiter know or email [email protected].Due to insurance coverage issues, we are unable to accommodate remote work from Hawaii or Alaska at this time.
Internal Employees
If you are a current employee, do not apply here - please navigate to our Internal Job Board in Greenhouse to apply to our open roles.

Top Skills

AWS
Hive
Pyspark
Python
PyTorch
Scikit-Learn
Snowflake
SQL
TensorFlow

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