Job Summary

We're looking for a data-driven Data Analyst who is hands-on with SQL and Python to work closely with the operations team. You'll work directly with large lending datasets (LOS/LMS) — querying, cleaning, modelling, and analysing them to generate actionable insights that improve loan disbursal efficiency, portfolio quality, and customer experience.

Key Responsibilities

- Write complex SQL queries (joins, window functions, CTEs, subqueries) to extract and manipulate data from relational databases and LOS/LMS systems.
- Use Python (Pandas, NumPy) for data cleaning, transformation, automation of recurring reports, and exploratory data analysis on large datasets.
- Work with raw, messy, multi-source datasets — identify data quality issues, handle missing/inconsistent data, and build repeatable data pipelines.
- Track and analyse key metrics such as CPL/CPA, delinquency rates, approval rates, and turnaround time (TAT) using SQL/Python-driven analysis.
- Perform statistical analysis on lending datasets to identify trends, patterns, and early warning risk indicators for the Credit/Risk team.
- Automate manual reporting workflows using Python scripts to improve accuracy and turnaround time.




- Support Collections and Sales teams with performance analytics and campaign effectiveness tracking through data modelling.
- Identify process gaps and recommend data-backed improvements across the loan lifecycle.

Required Qualifications & Experience

- Bachelor’s degree in computer science, Statistics, Economics, or a related field. 1–2 years of experience as a Data Analyst, preferably in BFSI/NBFC/Fintech.
- Strong hands-on proficiency in SQL — must be comfortable writing and optimizing complex queries on large relational databases.
- Working proficiency in Python for data analysis (Pandas, NumPy) — scripting for data cleaning, automation, and EDA is a core requirement, not just a plus.
- Proven experience working with large, real-world datasets — extraction, wrangling, and analysis.
- Working knowledge of LOS/LMS systems and personal loan business processes is a robust plus.
- Strong analytical thinking with attention to detail and accuracy.
- Good communication skills to translate data insights for non-technical stakeholders.
- Exposure to statistical concepts (hypothesis testing, correlation, regression) is an added advantage.

Interested Candidates can whatsapp resume on +91-XXXXXXXXXX

Pay: Up to ₹650,000.00 per year

Benefits:

- Provident Fund

Work Location: In person

📌 Data Analyst (India)
🏢 Kasar credit and capital private
📍 India