Senior Data Analyst - LAP

Krazy Bee Services; Bengaluru; On-site; INR 1,200,000 - 2,400,000; Full time

Job summary

Krazy Bee Services in Bengaluru, India, seeks a Data Analyst/Senior Data Analyst to shape the LAP portfolio by delivering data-driven insights across business, credit, collections, customer behavior, and channel performance. You will own end-to-end MIS, dashboards, deep-dive analysis, and predictive insights in collaboration with Sales, Credit, Risk, Operations, Finance, and HR.

The role requires solid SQL and Python, experience with Power BI or Tableau, understanding LAP metrics (LTV, FOIR,

Qualifications

• Bachelor / Master’s degree from reputed institution.
• 2-4 years of analytics experience in lending ideally with a Fintech, NBFC, or Digital Lending platform.
• Strong command of SQL and Python for data analysis and modeling.
• Experience with BI tools like Power BI or Tableau.
• Understanding of LAP-specific metrics (LTV, FOIR, delinquency buckets, etc.).
• Exposure to LOS/LMS/lending systems.
• Strong business acumen, with the ability to convert data into strategy.
• Experience working in agile, cross-functional product and tech environments.

Responsibilities

• Deliver and track daily performance and share insights to Sales, business teams, and senior leadership.
• Provide deep-dive analysis on metrics like yield, NPAs, bounce rates, TATs, and approval/rejection ratios.
• Build and maintain dashboards covering productivity, business metrics, stage-wise funnel tracking & TAT, and branch-level portfolio analysis.
• Track P&L performance against budgets; analyze variances with Finance and provide actionable feedback.
• Partner with Credit and Risk teams to refine underwriting rules using data.
• Analyze borrower profiles to optimize approval rates and minimize delinquencies.
• Conduct quality-of-leads and approval/rejection analyses; foreclosure analysis; leverage bureau data for benchmarking.
• Segment customers to drive targeting and engagement; analyze channel partner productivity and sourcing quality.
• Own manpower mapping and hiring analysis to support workforce planning.
• Evaluate pricing effectiveness using portfolio performance data and competitor benchmarking.
• Use funnel data to identify drop-offs and TAT issues; suggest workflow enhancements; validate data flow for new features.
• Drive MIS automation for recurring reports and dashboards.

Skills

SQL

Python

BI dashboards

Data analysis

Agile

Cross-functional teamwork

Education

Bachelor / Master’s degree

Tools

Power BI

Tableau

LMS/LOS systems

Job description

About the role:

About the role: The Data Analyst/Senior data analyst will play a pivotal role in shaping the LAP portfolio

strategy by delivering data-driven insights across business, credit, collections, customer

behavior, and channel performance. The role owns end-to-end MIS, dashboarding, deep-dive

analysis, and predictive/strategic insights partnering with Sales, Credit, Risk, Operations,

Collections, Finance, and HR to drive performance, process efficiency, and portfolio quality for

the LAP business.

Key Responsibilities

1. Business & Performance Analytics

• Deliver and track daily performance and share insights to Sales, business teams, and senior leadership.
• Provide deep-dive analysis on key metrics yield, NPAs, bounce rates, TATs, and approval/rejection ratios.
• Build and maintain dashboards covering productivity, business metrics, stage-wise funnel tracking & TAT, and branch-level portfolio analysis.

2. P&L & Financial Analysis

• Track P&L performance against budgets; analyze variances with Finance and provide regular, actionable feedback.

3. Risk & Credit Insights

• Partner closely with Credit and Risk teams to help refine underwriting rules using data.
• Analyze borrower profiles to optimize approval rates and minimize delinquencies.
• Conduct regular, extensive quality-of-leads and approval/rejection analysis.
• Conduct foreclosure analysis and share insights with business and leadership.
• Leverage bureau data (CIBIL/CRIF) for opportunity assessment and benchmarking at alocation/branch level.
• Leverage alternate data sources (GST, bank statements, property valuation) for deeper credit and risk insights.

4. Customer & Channel Analytics

• Segment customers using demographic, financial, and behavioral data to drive targeting and engagement.
• Analyze channel partner, productivity, and quality of sourcing to support channel optimization.
• Own payout and incentive data support/reconciliation; generate insights and design data- backed contests to improve productivity and activation.
• Oversee EMI-calling allocation and track feedback for insights

5. Manpower, Hiring Workforce Analytics

• Own manpower mapping at case-level and branch-level, with regular reconciliation.
• Own hiring analysis and insights on a regular basis to support workforce planning.

6. Product & Pricing Strategy

• Evaluate pricing effectiveness using portfolio performance data and competitor benchmarking.
• Analyze the impact of product changes on conversion, risk, and profitability.

7. Process & Funnel Optimization

• Use funnel data to identify drop-offs and TAT issues across the digital LOS/LMS journey.
• Recommend workflow enhancements using data, to improve user experience and reduce operational friction.
• Validate data flow for any new system feature and reconcile backend data
• Drive field additions in systems to reduce manual data-gathering effort.
• Drive MIS automation for recurring reports and dashboards to reduce manual effort.

8. Leaderboards, Scorecards & Predictive Models

• Create leaderboards and scorecards at various levels productivity, login, hiring, and approval rates/quality of sourcing.
• Build models to define targets and run prediction analysis

9. Alternate Data Analysis

• Leverage alternate data sources (GST, bank statements, bureau data, property valuation) for deeper business and credit insights.

Required Skills & Qualifications

• Bachelor /Master's degree from reputed institution
• 2-4 years of analytics experience in lending ideally with a Fintech, NBFC, or Digital Lending platform.
• Strong command of SQL and Python for data analysis and modeling.
• Experience with BI tools like Power BI or Tableau.
• Understanding of LAP-specific metrics (LTV, FOIR, delinquency buckets, etc.).
• Exposure to LOS/LMS/lending systems.
• Strong business acumen, with the ability to convert data into strategy.
• Experience working in agile, cross-functional product and tech environments.

Good to Have

• Exposure to bureau data analytics (CIBIL, CRIF)
• Experience with alternate data (e.g., GST, bank statement parsing)

This job description is intended to outline the general nature and key responsibilities of the position. It is not intended to be an exhaustive list of all duties, responsibilities, or qualifications associated with the role. The responsibilities and qualifications described may be subject to change, and other duties may be assigned as needed. Employment is at-will, meaning the employee or the employer may terminate the employment relationship at any time, with or without cause, and with or without notice.

Data Utilization Disclaimer

By applying for this position, you acknowledge and agree that any personal data you provide may be used for recruitment and employment purposes. The data collected will be stored and processed in accordance with our privacy policy and applicable data protection laws. Your information will only be shared with relevant internal stakeholders and will not be disclosed to third parties without your consent, unless required by law.