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Klimb.io

Posted 16 Sep 2026

Data Science Manager

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Employment
Full time
Team
Data Science & Analytics
Posted
16 Sep 2026

About the role

We are looking for a highly analytical and data-driven professional who can help strengthen our analytics capabilities, build scalable data solutions, and contribute to business growth through actionable insights and predictive decision-making.


Responsibilities:

  • Define, manage, and continuously refine the analytics roadmap aligned with business objectives.
  • Build, deploy, and maintain scalable data infrastructure, including data warehouses and data marts.
  • Develop and maintain predictive models and scoring infrastructure to support decision-making systems.
  • Identify opportunities to leverage alternative data sources for improving predictive capabilities.
  • Partner with cross-functional business teams to design and execute experiments focused on: Customer acquisition, churn reduction, delinquency control, and profitability improvement.
  • Generate actionable insights through automated reporting, dashboards, MIS, and analytical queries.
  • Monitor model and business performance metrics and recommend optimization strategies.
  • Ensure data accuracy, consistency, and reliability across reporting systems.


Requirements:

  • 2+ years of hands-on analytics experience in a fintech, financial services, startup, consulting, or related environment.
  • Strong proficiency in SQL and Python.
  • Good understanding of analytical problem-solving frameworks and data-driven decision-making.
  • Hands-on experience with data management, deployment, and performance monitoring frameworks.
  • Exposure to experimentation methodologies such as A/B testing or test-and-learn approaches.
  • Ability to work with large datasets and derive meaningful business insights.
  • Strong communication and stakeholder management skills.
  • Self-driven, detail-oriented, and comfortable working in a fast-paced environment.


Preferred Skills:

  • Experience in fintech, lending, BNPL, or risk analytics domains.
  • Familiarity with BI/reporting tools and dashboarding platforms.
  • Knowledge of predictive modeling, customer analytics, and behavioral scoring models.

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