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SeniorFull-timeGit
Salary Range
$143,650 - $194,350 /year
This salary is estimated based on similar roles. The actual salary may vary.
About the Role
We are seeking an experienced Home Loans Data Analyst to own end-to-end analytics for our residential mortgage portfolio. This role involves translating performance insights into measurable feedback loops that improve lending strategies.
Key Responsibilities
- →Define and maintain portfolio performance KPIs across credit, profitability, and risk
- →Perform cohort/vintage and segmentation analysis by various credit metrics
- →Build and maintain executive dashboards and automated reporting
- →Partner with Data Engineering to define data requirements and create new data sources
- →Monitor and report portfolio concentration limits and emerging risk exposures
- →Develop early warning indicators that proactively identify deteriorating performance
- →Track portfolio risk related to market shifts and quantify impact to credit outcomes
- →Order, track, and report refreshed collateral values across the portfolio
- →Conduct gap analyses across investor guidelines and product types
- →Review loan defects, exceptions, and deficiencies; perform root-cause analysis
- →Create a closed-loop learning system to identify drivers of performance and recommend strategy changes
- →Partner with Product, Data Engineering, and business stakeholders to deliver analytics solutions
- →Lead the execution of analytics initiatives using structured project practices
- →Ensure data integrity through metric definitions, reconciliations, QA checks, and consistent reporting
Requirements
- ✓Portfolio analytics expertise: segmentation, vintage analysis, trend attribution, and performance driver identification
- ✓Decision science mindset: hypothesis-driven analysis, measurement design, and quantifying trade-offs
- ✓Data rigor: reconciliation discipline, metric governance, documentation, and repeatable processes
- ✓Business translation: turning analysis into clear actions for underwriting strategy, policy changes, and operational improvements
- ✓Influence without authority: partnering across Underwriting, Ops, Compliance, Capital Markets, and Product to implement change
- ✓Execution strength: delivering analytics products reliably and improving them over time
Preferred qualifications
- ✓Advanced degree (MS/MBA/PhD) in a quantitative field
- ✓Familiarity with modern data stacks (Snowflake/BigQuery/Redshift, dbt, Airflow) and version control (Git)
- ✓Experience supporting capital markets needs
- ✓Experience designing and evaluating policy tests/experiments
- ✓Tools: JIRA/Confluence, Airtable, and project planning practices for analytics delivery
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