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Data Product Manager – Lending & Pay Later

Astra Tech
Abu Dhabi Emirate, UAE
fulltime
Mid-Senior
2 months ago
Product StrategyRoadmap PlanningMarket ResearchUser Story MappingAgile MethodologiesJira
Free

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Role Summary

We are looking for a

Data Product Manager

to build and manage the data ecosystem powering our

lending and pay later products

.

The ideal candidate will have experience in

micro-lending or digital credit platforms

, with a deep understanding of how

data flows through the lending lifecycle

— from origination to repayment.

You will define how data is collected, structured, and leveraged for

credit decisioning, business insights, and AI deployment

, ensuring that data becomes a core enabler for smarter, faster lending decisions.

Key Responsibilities

  • Own the
  • data roadmap
  • across the lending and pay-later ecosystem.
  • Map and manage all
  • data sources
  • involved in the
  • credit lifecycle
  • (KYC, transaction, repayment, behavioral, and bureau data).
  • Design and optimize
  • data pipelines
  • that support credit scoring, risk modeling, and AI systems.
  • Collaborate with Product, Engineering, and Data Science teams to ensure
  • data integrity, accessibility, and usability
  • .
  • Define data requirements for new products, features, and risk models.
  • Build
  • dashboards and metrics
  • to monitor portfolio performance and business health.
  • Enable
  • AI and ML model deployment
  • by ensuring high-quality, structured, and real-time data availability.
  • Partner with compliance and BI teams to ensure
  • data governance
  • and regulatory alignment.

Key Requirements

  • **5+ years of experience**
  • in data or product management roles within
  • lending, BNPL, or fintech ecosystems
  • .
  • Strong understanding of
  • credit data, decision engines, and lending workflows
  • .
  • Experience with
  • data platforms, APIs, and BI tools
  • (e.g., Snowflake, BigQuery, Power BI, or Looker).
  • Familiarity with
  • AI/ML use cases in credit risk, collections, and personalization
  • .
  • Strong analytical mindset with ability to translate business needs into scalable data solutions.
  • Proven cross-functional collaboration skills with product, data, and risk teams.

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