Senior Data Analyst

We are looking for a highly analytical and business-focused Data Analytics professional to drive Collections Analytics for a leading NBFC. This role will play a critical part in portfolio monitoring, delinquency analysis, collections strategy, performance optimisation, and data-driven decision-making across collections operations. The ideal candidate will have strong expertise in SQL, Python, Data Modelling, BI Visualisation, and Lending Analytics, along with deep domain knowledge of collections, delinquency management, and portfolio risk within Banking, NBFC, or FinTech environments.

The candidate will have responsibilities across the following functions:

Collections Performance Analytics:

• Analyse collection performance across products, geographies, agencies, and collection channels.
• Monitor and improve key collections metrics, including: Roll Rates, Cure Rates, Resolution Rates, Channel Efficiency, Promise-to-Pay (PTP) Effectiveness.
• Identify operational leakages and opportunities to improve collection outcomes.
• Generate actionable insights to optimize collections efficiency.

Portfolio Monitoring and Risk Analytics:

• Track delinquency movement across DPD buckets.
• Perform: Vintage Analysis, Cohort Analysis, and Flow Rate Analysis.
• Monitor early warning indicators and emerging portfolio risks.
• Analyse borrower behaviour patterns leading to delinquency and defaults.
• Support proactive portfolio risk management initiatives.

Dashboarding and Business Reporting:

• Develop and maintain automated dashboards and MIS reports for leadership teams.
• Build self-service reporting solutions using Tableau and modern BI tools.
• Enable real-time reporting and business visibility.
• Ensure data accuracy, consistency, and governance across reporting systems.

Collections Strategy and Decision Support:

• Partner with collections strategy teams to drive segmentation and targeting initiatives.
• Identify customer segments for differentiated collection treatments.
• Measure the effectiveness of collection campaigns and recovery interventions.
• Conduct A/B testing and impact analysis of collections strategies.
• Recommend data-backed improvements to collections processes.

Stakeholder Management:

• Collaborate closely with: Collections Operations, Risk Teams, Product Teams, Technology Teams, and Finance Teams.
• Present analytical findings and recommendations to senior leadership.
• Translate business problems into scalable analytical solutions.

Must-Have Technical Skills:

• Data and Analytics: Advanced SQL (Mandatory).
• Strong Python for Data Analysis and Automation.
• Data Modelling and Data Warehousing.
• Experience handling large-scale datasets (millions of records).
• Visualisation and Reporting: Tableau, Power BI, Advanced Excel, Power Query, Pivot Tables, Advanced Formulas.

Databases and Data Platforms:

• Experience working with: Oracle, PostgreSQL, Hadoop/Hive.
• Exposure to cloud data platforms such as Amazon Redshift and Snowflake.

Analytics and Modelling:

• Strong understanding of Classical Statistical Models.
• Advanced Machine Learning concepts.
• Predictive Analytics.
• Collections Modelling.
• Scorecard Development.

Domain Expertise Required:

• Strong understanding of: Lending and Collections Lifecycle, Retail Lending Products, Delinquency Management, Portfolio Risk Monitoring, Recovery Analytics.
• Hands-on experience with: DPD Buckets, Collections Workflows, Recovery Strategies, Portfolio Risk Metrics, and Collections Operations Analytics.

Data Engineering and Automation:

• Extract, transform, and analyse data from: Loan Management Systems (LMS), Collection Management Platforms, CRM Systems.
• Automate recurring reports and operational dashboards.
• Improve reporting efficiency through scripting and workflow automation.
• Partner with Data Engineering teams to improve data quality and data availability.

Preferred Experience:

• Candidates from NBFCs, Banks, Digital Lending, or FinTech companies with experience in: Personal Loans, Business Loans, Vehicle Loans, Home Loans, Credit Risk Analytics, and Collections Analytics.
• Additional preference for candidates with exposure to: Collection Dialer Systems, Digital Collections Platforms, Predictive Recovery Models, Behavioural Risk Analytics.

Education:

• Required: Bachelor's Degree in Engineering, Statistics, Mathematics, Economics, Computer Science, or related quantitative discipline.
• Preferred: MBA / PGDM, Master's in Analytics, Data Science, Statistics, or related field.

Ideal Candidate Profile:

• 5-10+ years of experience in Analytics, Collections Analytics, Risk Analytics, or Lending Analytics.
• Strong SQL + Python expertise.
• Deep Collections / Delinquency Management domain knowledge.
• Hands-on Tableau dashboarding experience.
• Experience working with large lending portfolios.
• Ability to influence business decisions through data-driven insights.

Skills

Power BI, Python, SQL, Tableau