Data Analytics

3 days ago

Ahmedabad, Gujarat, India ProClink Full time ₹ 5,00,000 - ₹ 12,00,000 per year

About the Role

We are seeking a highly motivated Senior Analyst/Consultant with strong expertise in Advanced SQL and Excel to join our Data Analytics team. The ideal candidate will have prior experience in the credit cards and BFSI domain, with a deep understanding of customer behavior, portfolio performance, and risk/collections strategies. This role involves working closely with business stakeholders to deliver insights, build analytical solutions, and drive data-informed decisions.

Key Responsibilities

  • Extract, manipulate, and analyze large datasets using Advanced SQL and Excel.
  • Work on portfolio analytics: acquisition, usage, delinquency, attrition, and profitability.
  • Conduct deep-dive analyses to identify business opportunities, risks, and areas of improvement.
  • Support the design and monitoring of campaigns, risk models, and customer engagement strategies.
  • Collaborate with cross-functional teams including product, risk, finance, and marketing to implement analytical solutions.
  • Ensure high standards of data quality, governance, and accuracy in reporting and analysis.

Required Skills & Qualifications

  • Bachelor's/Master's degree in Statistics, Economics, Mathematics, Engineering, or related field.
  • 3–6 years of experience in data analytics, preferably in the credit cards / payments / banking domain.
  • Strong expertise in Advanced SQL (writing complex queries, optimizing performance, working with large datasets).
  • Proficiency in Advanced Excel (pivot tables, complex formulas, macros, VBA preferred).
  • Good understanding of credit card lifecycle (acquisition, usage, risk, collections, retention).
  • Strong analytical mindset with the ability to translate data into actionable business insights.
  • Excellent communication and presentation skills to interact with stakeholders.

Preferred Skills (Good to Have)

  • Prior consulting or client-facing experience in BFSI analytics.
  • Knowledge of statistical techniques and exposure to Python/R/SAS.
  • Ability to design and deliver data-driven insights, dashboards, and reports to support decision-making.

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