Senior Data Analyst, Servicing

📋 Description

• Develop and execute robust data models that convert raw servicing logs into structured, "gold-standard" datasets. You will guarantee that our servicing data is clean, well-organized, and optimized for reporting and advanced analytics.

• Create and sustain scalable frameworks to track delinquency trends, roll rates, and recovery performance utilizing the structured datasets you have built.

• Enhance our analytics capabilities by crafting high-performance BigQuery SQL and designing user-friendly Tableau dashboards that enable stakeholders to make data-driven decisions in real-time.

• Establish and document standardized data schemas that facilitate repeatable insights across the organization, ensuring a "single source of truth" for all metrics related to servicing.

• Function as the analytical backbone for the Servicing team, translating intricate operational workflows into logical data structures that yield measurable financial outcomes.

⛳️ Requirements

• 3–5+ years of experience utilizing data to create measurable business impacts, particularly within loan servicing, collections, or operational analytics.

• Extensive expertise in SQL (preferably BigQuery); you excel at managing complex joins, subqueries, and window functions to reconstruct borrower payment histories and lifecycle events.

• Demonstrated ability to design and maintain structured datasets and schemas that convert disorganized operational logs into clean, reliable tables for servicing performance.

• You don’t merely report data; you create intuitive dashboards that assist managers in visualizing roll rates, delinquency categories, and agent productivity.

• Strong knowledge of servicing-specific metrics such as Net Charge-Offs (NCO), recovery rates, payoff behaviors, and loss mitigation effectiveness.

• Proven success in a fintech or financial services environment, with a thorough understanding of how servicing data integrates into broader Credit/Risk and Capital Markets strategies.

• Familiarity with Python for data manipulation, automating recurring servicing reports, or conducting ad-hoc cohort analyses.

• Understanding of experimental design for A/B testing in collections strategies.

• Clear and confident ability to communicate complex servicing trends into actionable insights for both technical teams and operational leadership.

• Comfort in navigating the uncertainties of a fast-paced environment and the capacity to establish analytical direction when servicing workflows or regulations change.

🏝️ Benefits

• Comprehensive medical, dental, and vision coverage, with 100% employer-paid premiums for employees and their dependents on select plans

• Company HSA, FSA, Dependent Care FSA, 401(k), and commuter benefits

• Employer-paid life and disability insurance

• 11 observed holidays and PTO plan

• Up to 12 weeks of paid family leave

• Continuing education reimbursement