The team

SoFi’s Credit team manages credit risk activities for our lending products (Student Loan Refinance, Private Student Loan, Personal Loan, Credit Card, and Mortgage) - including credit strategies/policies for new account origination and portfolio management, collections/recovery strategies and operations, and risk and operational data science and analytics. The team designs data-driven strategies to ensure the growth in lending is consistent with the company’s risk appetite and helps create the products and experiences that put our members’ interests first.

The Senior Credit Manager will work in the Credit team and have responsibilities to analyze and evaluate data to develop and propose value-added credit risk strategies and models for SoFi’s lending products, including Personal Loan, Student Loan Refinance, Private Student Loan, and Credit Card. The initial focus of the role will be on Personal Loan but the candidate may get opportunities to work on other lending products in the future. 

The candidate will be responsible for independently developing and implementing Personal Loan underwriting strategies that meet our risk appetite, monitoring and analyzing the risk trends within the portfolio to provide insights and recommendations for strategy enhancement opportunities. She/he will be part of the Credit team with 1LOD responsibilities.

The Senior Credit Manager will collaborate with cross-functional teams such as Business Units, Operations, Marketing, Finance, Capital Markets, Product, Engineering, Legal and Compliance. Use business acumen, credit experience and quantitative and analytical skills to drive revenue, control risk, and provide value to the company and consumers.

The ideal candidate will possess a data-driven analytics background and the strategic acumen to direct a function that draws strategic insights from data using database and statistical analysis tools to inform decisions and support SoFi’s overarching strategic goals relative to loss prevention and profit optimization. They bring new ways of thinking, data sources, technologies, and capabilities to SoFi. 

What you’ll do:

• Innovate… Bring your brightest ideas to build algorithmic risk strategies. This means you will architect credit underwriting, pre-screen targeting, and risk tier assignment.
• Data Driven… Your deep analysis will power the future of lending with an optimal real-time data ecosystem – including multi-product internal, bureau, third-party, and alternative data sources and uses.  
• Iterate, learn, innovate… We are all responsible for innovation and must embrace a test-and-learn mentality and data-driven decision making.
• Collaborate… Work collaboratively with business partners such as Business Units, Operations, Marketing, Finance, Legal and Compliance to deliver successful business results. Partner closely with implementation teams to accurately drive new strategies to production. 
• Control the Risk and Drive Performance Outcomes … Understand credit risk and develop approaches to mitigate loss and responsibly grow revenue. Monitor the performance of strategies and portfolios. Document and communicate results and escalate issues as necessary. Identify gaps/opportunities and drive actions.  
• Challenge the Status Quo … Challenge others, continuously raise the bar, build better processes and attack hard problems to help us build the best products in the industry. 
• Grow, Grow, Grow!… Be inspired by dynamic leaders and our rapidly growing business.  We want YOU to be an inspired leader of tomorrow, so we are recruiting the best, brightest, and passionately quantitative team members.  

What you’ll need:

• 7+ years of unsecured credit risk and data science experience
• Business acumen and work experience in the consumer lending business (loans or credit cards)

• Direct experience in the credit strategy analytical life cycle, including strategy and decision tree development, P&L, presentation, implementation validation, and post-implementation monitoring

• Proven analytical skills in conducting sophisticated analysis using customer performance data, bureau attributes, and other 3rd party variables to solve business problems
• Advanced SQL and Python skills for segmentation and vintage analysis, PD/LGD/EAD risk modeling (e.g. decision trees, logistic regression) and back-testing, rapid prototyping, feature engineering and pipeline development/operationalization
• A demonstrated ability to synthesize and communicate analysis to business partners and senior management
• Results-driven analytical approach, eagerness to learn, and ability to work collaboratively in a fluid environment
• Statistically rigorous experiment design and inferential evaluation
• Experience in developing custom credit features using data sources such as internal cross-product data, bank transaction, and other alternative data
• Advanced degree (Master’s or PhD) with a quantitative major such as Statistics, Mathematics, Engineering, or Computer Science

SoFi’s Credit team manages credit risk activities for our lending products (Student Loan Refinance, Private Student Loan, Personal Loan, Credit Card, and Mortgage) - including credit strategies/policies for new account origination and portfolio management, collections/recovery strategies and operations, and risk and operational data science and analytics. The team designs data-driven strategies to ensure the growth in lending is consistent with the company’s risk appetite and helps create the products and experiences that put our members’ interests first.

The Credit Strategy Lead will work in the Credit team and have responsibilities to analyze and evaluate data to develop and propose value-added credit risk strategies and models for SoFi’s lending products, including Personal Loan, Student Loan Refinance, Private Student Loan, and Credit Card.

The Credit Strategy Lead will collaborate with cross-functional teams such as Business Units, Capital Markets, Product and Engineering, and use business knowledge and quantitative and analytical skills to drive revenue, control risk, and provide value to the company and consumers.

The ideal candidate will possess a data-driven analytics background and the strategic acumen to direct a function that draws strategic insights from data using database and statistical analysis tools to inform decisions and support SoFi’s overarching strategic goals relative to loss prevention and profit optimization. They bring new ways of thinking, data sources, technologies, and capabilities to SoFi.

What you’ll do:

• Innovate… Bring your brightest ideas to building risk strategies. This means you will architect the pre-screen and underwriting strategies.
• Data Driven… Your deep analysis will power the future of lending with an optimal real-time data ecosystem – including multi-product internal, bureau, third-party, and alternative data sources and uses.
• Iterate, learn, innovate… We are all responsible for innovation and must embrace data-driven decisions.
• Control the Risk and Drive Performance Outcomes … Understand credit risk and develop approaches to mitigate loss and responsibly grow revenue. Monitor the performance of strategies and portfolios. Document and communicate results and escalate issues as necessary. Identify gaps/opportunities and drive actions.
• Grow, Grow, Grow!… Be inspired by dynamic leaders and our rapidly growing business. We want YOU to be an inspired leader of tomorrow, so we are recruiting the best, brightest, and passionately quantitative team members.

What you’ll need:

• 4+ years of related experience
• Business acumen and work experience in the consumer lending business (loans or credit cards)
• Direct experience in the credit strategy analytical life cycle, including strategy and decision tree development, presentation, implementation validation, and post-implementation monitoring
• Proven analytical skills in conducting sophisticated analysis using customer performance data, bureau attributes, and other 3rd party variables to solve business problems
• Proficient skills in Excel, SQL and Python
• A demonstrated ability to synthesize and communicate analysis to business partners and senior management
• High motivation to drive results, eager to learn, and able to work collaboratively in a fluid environment
• Knowledge/skills in analytical and modeling techniques such as Decision Trees, regression, logistic regression, A/B Testing, and Tableau
• Preferred: 4+ years of consumer lending credit strategy work experience
• Preferred: Experience in analyzing and testing credit strategies or models to meet the fair lending requirements
• Preferred: Advanced degree (Master’s or PhD) with a quantitative major such as Statistics, Mathematics, Engineering, or Computer Science

Senior Manager, Data Science

Portfolio Management and Loss Mitigation

The Role: 

SoFi is seeking an inspirational and deeply experienced Senior Manager to lead the Portfolio Management and Loss Mitigation function in our Risk Data Science team. Reporting to the Head of Risk Data Science, this role will lead the development, deployment, and governance of portfolio management and loss mitigation models for all credit products.

The ideal candidate is a hands-on leader 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 portfolio performance, reduce losses, and ensure rigorous adherence to Model Risk Management (MRM) standards. This role requires exceptional organizational leadership, an ability to influence stakeholders, and proven success in delivering complex models into a regulated production environment.

What You'll Do: 

• Portfolio Management and Loss Mitigation Excellence: Directly oversee the development and deployment of Next Generation models designed to manage and mitigate portfolio losses while maintaining loss guardrails.
• 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.
• Alternative Data Strategy: Spearhead the evaluation and integration of alternative data sources (Macro-Economic variables, tri-bureau, LexisNexis, cash flow data) to enhance predictive power across all credit products.
• 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.
• 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 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 to create scalable and auditable infrastructure.

What You'll Need:

• Experience: 8+ years of progressive experience in credit risk, modeling, and data science within a regulated financial institution (FinTech, Bank, or similar), with at least 3 years in a people management role, managing technical staff.
• 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).
• 3+ years of progressive people management experience is required, including the ability to recruit, mentor, and foster talent within a team of high-performing Staff and Senior Data Scientists.
• Communication: Ability to distill highly complex analytical concepts into clear, concise, and compelling narratives for non-technical leadership.

The role:

We are seeking a highly experienced AI Automation Lead with 8+ years of engineering experience to bridge the gap between sophisticated data ecosystems and high-performance user applications. This role is responsible for architecting and delivering our multi-agent AI strategy—moving beyond simple chatbot implementations to autonomous, stateful workflows that solve complex, real-world business problems.

This individual operates as a true full-stack product engineer, equally comfortable working across frontend, backend, data orchestration, and AI systems. You will define the technical vision for AI-driven automation, ensuring solutions are scalable, production-grade, and highly available.

What you’ll do:

AI Architecture & Agentic Workflows

• Design and implement multi-agent AI workflows that enable coordinated task execution across systems (e.g., fraud detection, risk assessment, financial modeling)

• Build human-in-the-loop systems that allow users to monitor and intervene in automated processes

• Integrate Snowflake Cortex for in-database AI workloads, including LLM functions, vector search, and ML processing

Full-Stack Engineering

• Develop complex, data-rich user interfaces using React to visualize and control AI workflows

• Build scalable backend services in Python with a focus on performance, concurrency, and clean API design

• Orchestrate workflows and automation pipelines using Apache Airflow

Data & Infrastructure Strategy

• Leverage Snowflake and dbt to ensure clean, governed, and high-performance data pipelines

• Maintain infrastructure as code and CI/CD pipelines to enable reliable and rapid deployments

• Optimize performance and cost of LLM usage and internal AI systems

Technical Leadership

• Lead architectural decisions and set engineering standards across the team

• Conduct code reviews, mentor engineers, and promote a culture of ownership

• Partner with Product to translate business problems into scalable automation solutions

What you’ll need:

• 8+ years of professional software engineering experience

• Strong expertise in React with the ability to build complex, stateful UIs from scratch

• Deep expertise in Python, including async programming and AI/ML frameworks

• Experience building multi-agent systems or complex AI workflows (e.g., LangGraph, CrewAI, AutoGen, or similar)

• Hands-on experience with Snowflake, including data modeling and AI integrations

• Strong experience with Apache Airflow for workflow orchestration

• Working knowledge of CI/CD pipelines and containerization (Docker, Kubernetes)

• Proven ability to lead technical design and own end-to-end system delivery

Nice to have:

• Experience with Snowflake Cortex or in-database AI processing

• Experience fine-tuning or deploying custom ML models

• Background in fintech, risk, fraud, or financial systems

• Experience migrating manual processes into automated AI-driven systems

• Strong system design experience in distributed, production environments

The profile we’re looking for:

You are a full-stack AI systems architect who thrives on building end-to-end solutions—not just components. You move beyond traditional CRUD applications and focus on delivering intelligent, automated systems that solve meaningful business problems.

You take ownership of both the system and the user experience, ensuring that AI capabilities are not only powerful but usable and scalable. You can take an ambiguous goal—like automating a fraud review process—and turn it into a fully functional, multi-agent system with a robust user interface in a matter of weeks.

The Role
The Risk Data Science team is seeking a strategic and technically deep Machine Learning Engineer to lead the evolution of SoFi’s Home Loan and Home Equity risk frameworks. This role is at the center of a high-priority initiative to deliver a comprehensive, loan-level credit risk and valuation framework for our home lending portfolios. 

As a key technical leader, you will apply state-of-the-art ML methodologies to solve complex problems—including default and prepayment modeling, property valuation (AVMs), and credit risk assessment—ensuring our high-value secured loan products are backed by world-class data science.

What You’ll Do

• Lead the design and implementation of ML models for mortgage-specific use cases, including credit underwriting, debt-to-income (DTI) validation, and automated appraisal reviews.
• Provide technical oversight and end-to-end ownership of externally developed models, ensuring they meet rigorous internal standards for quality, performance, and scalability.
• Present model performance and portfolio insights to senior leadership, translating complex data into actionable credit and business strategies.
• Collaborate with Model Risk Management (MRM) and governance teams to ensure all models are developed with the technical rigor required to satisfy complex regulatory and compliance standards.
• Partner with Product and Engineering teams to operationalize models, overseeing deployment, real-time monitoring, and seamless integration into core business systems.
• Continuously explore and leverage in-house, external, and open-source ML frameworks to build the next generation of proprietary mortgage risk tools.

What You’ll Need

• Master’s degree in Computer Science, Statistics, Mathematics, Physics, Engineering, or a quantitative field required. Ph.D. preferred.
• 5+ years of direct experience with building, implementing, and deploying machine learning models within Home Loans or Home Equity lending environments.
• Expert knowledge of statistical modeling and ML methods, including linear/logistic regression, ensemble methods (XGBoost/LightGBM), clustering, and outlier detection.
• Strong programming skills in Python and SQL.
• Hands-on experience with ML model implementation in production environments using tools such as AWS SageMaker, Git, Docker, and CI/CD pipelines.
• Strong ability to distill complex technical methodologies into simple, persuasive terms for non-technical stakeholders.

Nice To Have

• Proven track record in technical model documentation and navigating the Model Risk Management lifecycle.
• Experience working in a cross-functional capacity across Product, Engineering, and Risk departments.

The Role

The Risk Data Science team is looking for a Data Scientist/Senior Data Scientist to develop advanced machine learning and statistical models, guide measurement, strategy, and data-driven decision making to support various credit risk and operational areas at SoFi. The Data Scientist will work closely with Credit, Risk, Product, Engineering, and Operations teams to design solutions for underwriting, portfolio management, loss mitigation, and loss forecasting etc. These tasks involve researching and applying state of the art modeling methodologies to solve complex business problems. This role is very rewarding as your work will have a direct and immediate impact on the business’ profitability.

What You’ll Do

• Develop, implement, and continuously improve machine learning and statistical models that support various credit, risk, and operational procedures including but not limited to underwriting, portfolio management, loss mitigation, and loss forecasting, etc.
• Present model performance and insights to Credit, Risk, and Business Unit leaders.
• Proactively identify opportunities to apply advanced modeling approaches to solve complex business problems.
• Explore and leverage in-house and external data sources to enhance model predictive power.
• Collaborate with the Model Risk Management team to demonstrate models are developed with high level rigor that satisfy Model Risk Management and Governance requirements. 
• Perform ongoing monitoring of the models through the construction of dashboards and KPI tracking
• Collaborate with the Product and Engineering teams to improve the model development, deployment, monitoring, and model re-calibration/re-build process..
• Explore and apply in-house and open-source machine learning and statistical tools and algorithms to develop and improve models.

What You’ll Need

• Master’s degree in Statistics, Econometrics, Mathematics, Operations Research, Physics, Computer Science, Engineering, or quantitative field required. PhD degree preferred.
• 2+ years of relevant work experience in building and implementing machine learning and statistical models.
• Excellent logic reasoning and communication abilities when interpreting business requirements and translating them into effective data solutions.
• Strong skills in writing efficient SQL queries and Python code to create complex attributes, especially with large datasets.
• Strong sensitivity to details in data and proactively investigate them to uncover unknown patterns.
• Strong knowledge of databases and related languages/tools such as SQL, NoSQL, Hive, etc. 
• Demonstrated sophisticated experience in building efficient and reliable pipelines that interact with large datasets stored in SageMaker and Snowflake, automating recurring processes such as data extraction and processing, feature selection, model training, model monitoring, and generating documentation templates to support reproducibility and cross-functional collaboration.
• Excellent knowledge of machine learning and statistical modeling methods for supervised and unsupervised learning. These methods include (but are not limited to) regression, classification, clustering, outlier detection, novelty detection, decision trees, nearest neighbors, support vector machines, ensemble methods and boosting, neural networks, deep learning and its various applications. Continuously following the advancement of machine learning and artificial intelligence to update your knowledge and skills in order to solve business problems with the most efficient methodologies
• Strong programming skills in Python and machine learning libraries (e.g., sklearn, lightgbm, xgboost, pytorch, tensorflow, keras, etc.)

Nice To Have

• Experience in a lending organization.
• Experience with model documentation and delivering effective verbal and written communication.
• Experience in working closely with Product, Engineering, and Model Risk Management teams.
• Experience with AWS or GCP.

The role:

We are seeking a visionary Home Loans and Commercial Valuation Strategy & Governance to serve as the organization’s definitive Subject Matter Expert (SME) on all things property value. In this high-impact role, you will be the architect of our enterprise valuation strategy across Conventional, Jumbo, FHA/VA/USDA, Closed-End Seconds (CES), HELOC, and Commercial (CRE/MF).

As the enterprise owner of valuation policy, you will design the "Valuation Engine" of the future—moving away from manual, one-size-fits-all workflows toward a sophisticated, risk-tiered approach that utilizes appraisals, evaluations, and AVMs based on data-driven complexity triggers. You will lead the transition to an analytics-led operating model, intervening directly on high-risk/complex files while automating the routine through rigorous governance.

What you’ll do: 

1. Property SME & Market Intelligence

Enterprise SME: Serve as the final authority on property valuation trends and risks across both Residential and Commercial (CRE/MF) asset classes.

Market Analysis: Maintain a deep understanding of the macro and micro-economic drivers of the housing and commercial markets.

Advisory: Provide strategic counsel to business line leaders and Credit Policy on how market shifts should impact lending appetite and collateral requirements.

1. HPI Oversight & Housing Surveillance Framework

Model Ownership: Exercise full oversight of House Price Index (HPI) models, ensuring they accurately capture market movements and volatility.

Surveillance Framework: Build and maintain a comprehensive Housing Surveillance Framework. Use HPI models and external data to monitor regional trends, identify price bubbles, and establish geographic "hot zone" triggers.

Proactive Risk Management: Integrate surveillance outputs directly into the "Valuation Engine" to automatically escalate scrutiny in volatile markets.

1. Valuation Strategy, Policy & Model Risk

Strategic Tiering: Define risk tiers and set coverage rules (Appraisal vs. Evaluation vs. AVM) based on exposure, complexity, and surveillance triggers.

The Policy Stack: Own and govern the complete policy suite, including Real-Estate Valuation, Evaluation Policy, Reconsideration of Value (ROV) Framework, and AVM Strategy.

Model Governance: Select and govern AVMs. Lead the program for testing, back-testing, and challenger modeling.

Quality & Fairness: Implement random-sample validation and bias/fairness checks. Publish performance scorecards and remediation plans to ensure alignment with OCC/Interagency guidance.

1. Strategic Partnerships & Execution

Cross-Functional Leadership: Coordinate with Credit Policy, Model Risk, Compliance/Fair Lending, and Originations/Servicing to drive a seamless, compliant valuation process.

RACI & Reporting: Define the enterprise RACI for valuation decisions; establish a monthly/quarterly reporting cadence for KRIs and KPIs to executive leadership.

What you’ll need:

• Experience: 15+ years of related experience in Real Estate Valuation, Housing Economics, or Collateral Risk Management.
• Education: Minimum Education Requirements such as:  Bachelor’s Degree or Higher
• SME Status: Deep technical knowledge of HPI modeling and a mastery of both Residential and Commercial property markets.
• Regulatory Mastery: Expert-level understanding of USPAP, Interagency Appraisal and Evaluation Guidelines, and AVM Quality Control expectations.
• Analytical Depth: Ability to build data-driven surveillance frameworks and manage complex model-risk environments.
• Influence: Proven ability to drive results through partnership, moving the organization toward a sophisticated, tech-enabled valuation future.
• Vision: A track record of transforming manual, legacy processes into tech-enabled, automated, and risk-sensitive operating models.

The role:

We are seeking a visionary Director of Strategic Bureau Business Manager to architect and lead our centralized framework for credit data engagement. In this high-impact role, you will move beyond traditional vendor management to build a high-leverage, diversified data ecosystem. You will be responsible for centralizing engagement with Credit Reporting Agencies (CRAs) and specialized FCRA vendors to streamline efforts, improve oversight, and accelerate innovation through modern cloud data environments.

Your mission is to transition the organization toward a hot-swappable data network where providers earn their place in our ecosystem through proven, measurable ROI and differentiated data assets.

What you’ll do: 

• Strategic Framework Leadership: Centralize all bureau engagement into a unified framework to provide strategic guidance, contractual leverage, and operational oversight across multiple product lines. Partner with Procurement and internal stakeholders to ensure maximum business value is received from each relationship.

• Value Chain Management: Coordinate a holistic view of the Credit Reporting Agency value chain, managing the relationship between the proprietary data we furnish to the bureaus and the specialized services we consume in return.

• Continuous Optimization & Data Quality: Execute a multi-year roadmap focused on spend efficiency and data integrity. Conduct comprehensive audits of data consumption and provide regular analysis of bureau performance, data quality metrics, and trends in credit reporting errors or opportunities.

• Risk & Compliance Stewardship: Implement and maintain appropriate risk management controls related to credit bureau relationships. Ensure all credit reporting and data usage practices comply with applicable laws and regulations, including the Fair Credit Reporting Act (FCRA) and GDPR.

• Drive Strategic Agility: Build and execute a roadmap that reduces technical barriers to entry for new data partners, ensuring the organization can agilely pivot between providers based on real-time data performance.

• Performance-Based Partnership Management: Establish a value-based incentive model for data providers. Prioritize partnerships with vendors who provide high-value, unique data assets that drive measurable lift in underwriting, collections, and fraud prevention.

• Collaborative Innovation: Partner closely with Risk, Data Science, and Engineering teams to conduct Value Discovery sessions, proving the worth of new data assets in an offline environment before committing to production integration.

• Strategic Liaison: Act as the primary business liaison and architect for relationships with major CRAs and auxiliary FCRA vendors. Stay informed on industry developments and bureau-specific rules to assess their impact on the organization.

What you’ll need:

• 12+ Years of Experience: Deep expertise in credit data ecosystems, bureau operations, or fintech risk management.

• Strategic Orchestration: A proven track record of managing multi-million dollar vendor relationships and navigating complex, large-scale RFP processes.

• Data-Forward Mindset: Proficiency in navigating modern data environments and the ability to translate complex data studies into executive-level business strategies.

• Expertise in Alternative Data: Strong understanding of the evolving landscape of differentiated data assets, including trended data, utility/telco, and cash-flow analytics.

• Regulatory Command: Comprehensive knowledge of FCRA, GDPR, and relevant compliance standards governing credit reporting and data usage.

• Influential Leadership: Exceptional ability to drive cross-functional alignment between technical and business teams to execute a unified data vision.

The Role

The Credit Bureau Business Analyst is a highly autonomous individual contributor responsible for owning bureau relationships, driving data-informed strategy, and executing against SoFi’s Credit Reporting Agency (CRA) initiatives.

This role sits at the intersection of credit data, vendor management, and business strategy—requiring someone who can move beyond reporting to analyze, influence, and drive decisions across the credit bureau ecosystem. You will work directly with bureaus (Experian, TransUnion, Equifax) and internal partners to optimize data usage, improve outcomes, and support risk and product strategies.

What You’ll Do

• Serve as the primary owner and point of contact for assigned credit bureau relationships, working directly with Experian, TransUnion, Equifax, and other data providers
• Drive end-to-end bureau execution and strategy for products and initiatives, including issue resolution, data quality improvements, and rule interpretation
• Use SQL and data analysis to identify trends, uncover root causes, and translate insights into actionable business recommendations
• Analyze credit data performance, dispute trends, and bureau feedback to proactively identify risks and optimization opportunities
• Partner cross-functionally with Risk, Product, Compliance, Legal, Disputes, Procurement, and Data teams to align on strategy and execution
• Lead and contribute to initiatives with department- and function-level impact, including new product onboarding and bureau-related programs
• Evaluate trade-offs and make principle-based decisions that balance risk, cost, and customer impact
• Support and enhance risk management and compliance controls related to credit data (FCRA and related regulations)
• Provide clear, concise reporting and insights to leadership, including performance trends, risks, and opportunities
• Proactively communicate progress, blockers, and escalations, operating with a high level of ownership and accountability

What You’ll Need

• Bachelor’s degree and 5+ years of relevant experience, or equivalent practical experience
• Direct experience working with credit bureaus (Experian, TransUnion, Equifax) or third-party credit data providers
• Demonstrated experience owning or directly managing external vendor or bureau relationships
• Hands-on experience using SQL to analyze data and support decision-making
• Proven ability to operate independently and drive cross-functional initiatives from problem identification through execution
• Strong analytical mindset with the ability to connect data insights to business impact
• Working knowledge of FCRA and GLBA
• Excellent communication skills, with the ability to influence stakeholders without direct authority
• Ability to thrive in ambiguous or evolving environments and drive clarity

Nice to Have

• Experience in risk strategy, credit strategy, or fraud strategy environments
• Experience supporting multiple products or business lines
• Exposure to vendor negotiations, procurement, or cost optimization initiatives
• Experience with disputes operations, audits, or regulatory reviews

The team

SoFi’s Credit team manages credit risk activities for our lending products (Student Loan Refinance, Private Student Loan, Personal Loan, Credit Card, and Mortgage) - including credit strategies/policies for new account origination and portfolio management, collections/recovery strategies and operations, and risk and operational data science and analytics. The team designs data-driven strategies to ensure the growth in lending is consistent with the company’s risk appetite and helps create the products and experiences that put our members’ interests first.

The Senior Credit Manager will work in the Credit team and have responsibilities to analyze and evaluate data to develop and propose value-added credit risk strategies and models for SoFi’s lending products, which include Personal Loan, Student Loan Refinance, Private Student Loan, and Credit Card. The initial focus of the role will be on Private Student Loan but the candidate may get opportunities to work on other lending products in the future.

The candidate will be responsible for independently developing and implementing underwriting strategies that meet our risk appetite, monitoring and analyzing the risk trends within the portfolio to provide insights and recommendations for strategy enhancement opportunities. She/he will be part of the Credit team with 1LOD responsibilities.

The Senior Credit Manager will collaborate with cross-functional teams such as Business Units, Operations, Marketing, Finance, Capital Markets, Product, Engineering, Legal and Compliance. Use business acumen, credit experience and quantitative and analytical skills to drive revenue, control risk, and provide value to the company and consumers.

The ideal candidate will possess a data-driven analytics background and the strategic acumen to direct a function that draws strategic insights from data using database and statistical analysis tools to inform decisions and support SoFi’s overarching strategic goals relative to loss prevention and profit optimization. They bring new ways of thinking, data sources, technologies, and capabilities to SoFi.

What you’ll do:

• Innovate… Bring your brightest ideas to build algorithmic risk strategies. This means you will architect credit underwriting, pre-screen targeting, and risk tier assignment.
• Data Driven… Your deep analysis will power the future of lending with an optimal real-time data ecosystem – including multi-product internal, bureau, third-party, and alternative data sources and uses.
• Iterate, learn, innovate… We are all responsible for innovation and must embrace a test-and-learn mentality and data-driven decision making.
• Collaborate… Work collaboratively with business partners such as Business Units, Operations, Marketing, Finance, Legal and Compliance to deliver successful business results. Partner closely with implementation teams to accurately drive new strategies to production.
• Control the Risk and Drive Performance Outcomes … Understand credit risk and develop approaches to mitigate loss and responsibly grow revenue. Monitor the performance of strategies and portfolios. Document and communicate results and escalate issues as necessary. Identify gaps/opportunities and drive actions.
• Challenge the Status Quo … Challenge others, continuously raise the bar, build better processes and attack hard problems to help us build the best products in the industry.
• Grow, Grow, Grow!… Be inspired by dynamic leaders and our rapidly growing business. We want YOU to be an inspired leader of tomorrow, so we are recruiting the best, brightest, and passionately quantitative team members.

What you’ll need:

• 7+ years of related experience
• Business acumen and work experience in the consumer lending business (loans or credit cards)
• Direct experience in the credit strategy analytical life cycle, including strategy and decision tree development, P&L, presentation, implementation validation, and post-implementation monitoring
• Proven analytical skills in conducting sophisticated analysis using customer performance data, bureau attributes, and other 3rd party variables to solve business problems
• Proficient data exploration and credit modeling skills in Excel, SQL and Python
• A demonstrated ability to synthesize and communicate analysis to business partners and senior management
• Results-driven, eager to learn, and able to work collaboratively in a fluid environment
• Knowledge/skills in analytical and modeling techniques such as decision trees, regression, logistic regression, test design
• Preferred: 7+ years of credit card or unsecured loan credit risk experience
• Preferred: Experience in developing credit strategies using innovative data sources such as cash flow or alternative data
• Preferred: Advanced degree (Master’s or PhD) with a quantitative major such as Statistics, Mathematics, Engineering, or Computer Science