Data Analyst
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Key skills for this role
Role Overview
The Data Analyst will drive collections portfolio performance through analytics, strategy, and business ownership.
The role works across Collections, Data, Product, and Operations to optimize recovery outcomes through data-driven decisions.
Key Skills for This Role
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About DPDzero
DPDzero is an AI-powered, full-stack collections platform for banks and non-bank financial companies.
The company uses AI agents, data science algorithms, and a zero-operations platform to improve loan collections.
About the Role
The Data Analyst will drive collections portfolio performance through analytics, strategy, and business ownership.
The role works across Collections, Data, Product, and Operations to optimize recovery outcomes through data-driven decisions.
Key Responsibilities
- Own performance tracking and analysis for collections portfolios.
- Support onboarding of new accounts and allocations.
- Analyze portfolio performance across segments, DPD buckets, and channels.
- Build dashboards and automated reports using SQL, Excel, and business intelligence tools.
- Lead weekly and monthly business reviews with actionable recommendations.
- Partner with Operations, Product, Finance, and Engineering teams.
- Validate allocation logic, revenue calculations, and reporting outputs.
- Perform ad hoc analyses and strategy evaluations to improve recoveries.
What We’re Looking For
- 2–5 years of experience in analytics, collections, lending, fintech, or business operations.
- Strong SQL and Excel skills; Python is preferred.
- Experience with large datasets, dashboards, and analytical frameworks.
- Strong problem-solving, communication, and presentation skills.
- Collections, credit risk, or portfolio analytics experience is a plus.
Why Join Us
- The role offers high ownership with direct visibility to leadership and clients.
- The analyst can influence collection strategy at scale and drive measurable recovery, revenue, and business growth outcomes.
- The position provides cross-functional exposure across Analytics, Product, Operations, and Data Science.
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