Senior Data Analyst, Servicing

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Senior Data Analyst, Servicing

#удаленка #senior

Company: Figure

Salary: $110k - $150k

🔹What You’ll Do

-Design and implement robust data models that transform raw servicing logs into structured, "gold-standard" datasets. You will ensure our servicing data is clean, organized, and optimized for both reporting and advanced analytics.

-Build and maintain scalable frameworks to monitor delinquency trends, roll rates, and recovery performance using the structured datasets you’ve engineered.

-Elevate our analytics toolkit by writing high-performance BigQuery SQL and designing intuitive Tableau dashboards that empower stakeholders to make data-driven decisions in real-time.

-Create and document standardized data schemas that make insights repeatable across the company, ensuring a "single source of truth" for all servicing-related metrics.

-Act as the analytical backbone for the Servicing team, translating complex operational workflows into logical data structures that drive measurable financial outcomes.

🔹What We Look For

-3–5+ years of experience using data to drive measurable business impact, specifically within loan servicing, collections, or operational analytics.

-Deep proficiency in SQL (preferably BigQuery); you are an expert at handling complex joins, subqueries, and window functions to reconstruct borrower payment histories and lifecycle events.

-Proven ability to design and maintain structured datasets and schemas that transform messy operational logs into clean, reliable tables for servicing performance.

-You don’t just report data; you build intuitive dashboards that help managers visualize roll rates, delinquency buckets, and agent productivity.

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

-Proven track record in a fintech or financial services environment, with a solid grasp of how servicing data feeds back into broader Credit/Risk and Capital Markets strategies.

-Working knowledge of Python for data manipulation, automating recurring servicing reports, or performing ad-hoc cohort analysis.

-Appreciation for experimental design for A/B testing collections strategies.

-Clear, confident ability to translate complex servicing trends into actionable insights for both technical teams and operational leadership.

-Comfort navigating the ambiguity of a fast-moving environment and the ability to set analytical direction when servicing workflows or regulations shift.

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