Commercial Loans Senior Data Analyst

The Role:

We are seeking an experienced technically strong Senior Data Analyst – Commercial Lending to own end-to-end analytics for our commercial lending portfolio and translate performance insights into a measurable feedback loop that improves credit strategy risk management and profitability.

In this role you will analyze portfolio performance across the full lifecycle (origination → underwriting → servicing → repayment/default outcomes) build scalable reporting and monitoring and partner closely with Credit Underwriting Risk Operations Finance Compliance and Product to turn data into actionable decisions.

You will define the “source of truth” for portfolio performance identify emerging risks and growth opportunities and drive data-informed changes to credit policy underwriting strategies pricing and operational processes—while measuring their impact.

What You’ll Do: 

• Define and maintain KPIs across credit risk growth and profitability (e.g. delinquency rates default rates loss rates recovery rates utilization yield risk-adjusted return metrics).
• Perform cohort/vintage and segmentation analysis across borrower attributes (industry revenue risk rating collateral type geography loan size term product type).
• Build and maintain executive dashboards and automated reporting that clearly explain performance trends drivers and recommended actions.
• Partner with Data Engineering to ensure scalable data models clean metric definitions and reliable reporting pipelines.

• Monitor portfolio concentrations across industries geographies borrower segments and product types.
• Develop and track early warning indicators (e.g. payment behavior changes utilization shifts covenant signals sector stress).
• Assess impact of macroeconomic and market conditions (rates sector performance liquidity trends) on portfolio risk and returns.

• Analyze credit policy performance and underwriting decisions identifying opportunities to optimize approval rates loss outcomes and risk-adjusted returns.
• Conduct root-cause analysis on defaults exceptions and losses; quantify business impact.
• Build a closed-loop system:
• Identify key drivers of performance
• Recommend changes (credit policy pricing underwriting limits)
• Partner to implement changes
• Measure impact through structured before/after analysis

• Evaluate risk vs. growth vs. profitability trade-offs across segments and products.
• Support pricing strategy and capital allocation decisions through data-driven insights.
• Analyze lifecycle economics (origination quality utilization retention loss timing recovery).

• Partner with Credit Risk Product Finance and Operations to deliver analytics solutions (dashboards datasets monitoring tools).
• Lead analytics initiatives with structured execution (requirements timelines stakeholder alignment QA rollout).
• Ensure data integrity and governance across all reporting and analytics outputs. 

• Strong technical data skills: advanced SQL (complex joins window functions performance optimization) and proficiency in Python (pandas numpy data manipulation statistical analysis). Experience building reproducible analysis and scalable datasets.
• Data modeling & analytics engineering: ability to work with large datasets design clean data structures and partner with Data Engineering on pipelines (e.g. dbt Airflow).
• 3 years of Commercial lending analytics expertise: portfolio segmentation credit performance analysis and lifecycle modeling.
• Decision science mindset: hypothesis-driven analysis experiment design and quantifying trade-offs (risk vs. growth vs. profitability).
• Data rigor: strong discipline around metric definitions reconciliation QA and documentation to ensure consistent reporting.
• Business translation: ability to convert complex analysis into clear actionable recommendations for credit strategy underwriting and product decisions.
• Cross-functional influence: ability to partner effectively with Credit Risk Finance Product and Engineering to drive change.
• Execution excellence: delivering high-quality dashboards datasets and monitoring tools with a focus on scalability and continuous improvement.

• Advanced degree (MS/MBA/PhD) in a quantitative field.
• Familiarity with modern data stacks (e.g. Snowflake/BigQuery/Redshift dbt Airflow) and version control (Git).
• Experience supporting capital markets needs: investor reporting securitization support due diligence credit tape analysis and guideline overlays.
• Experience designing and evaluating policy tests/experiments (A/B testing where applicable quasi-experimental measurement monitoring for unintended impacts).
• Tools: JIRA/Confluence Airtable and project planning practices for analytics delivery.

What We Do

SoFi wasn’t built to be a bank. Or a technology company. We were built for one mission: help people achieve financial independence so they can realize their ambitions. Redefining an entire industry isn’t easy work—and it’s not for the faint of heart. It takes a certain kind of team. People with diverse perspectives and expertise united by a common sense of purpose. People willing to challenge assumptions but always do the right thing. People proving that innovation and responsibility don’t have to compete but can come together to create something truly unconventional in the world. For the last eight years we’ve been charting this new path forward. We call it The SoFi Way. At SoFi we don’t just talk about culture: we live it. The SoFi Way is how we show up every day how we make decisions and how we build for our members clients and each other.

Why Work With Us

Together with our members we’re changing the way people think about and interact with personal finance. We’re a next-generation Fintech company using innovative mobile-first technology to help our members reach their goals. The industry is going through an unprecedented transformation and we’re at the forefront.

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