Senior Collection Data Analyst at Palmpay Limited

Dhaka, Dhaka Division, Bangladesh -

Full Time

Start Date

Immediate

Expiry Date

28 Mar, 26

Salary

0.0

Posted On

28 Dec, 25

Experience

2 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

SQL, Data Extraction, Data Analysis, Reporting, Excel, Data Visualization, KPI Tracking, Performance Optimization, Collaboration, Problem Solving, Communication, Financial Services, Collection Operations, Loan Lifecycle, Risk Metrics

Industry

Financial Services

Description

About PalmPay PalmPay is a leading neobank and fintech platform scaling financial inclusion across emerging markets. With over 40 million users, we are building a digital financial ecosystem that empowers individuals and businesses through accessible, easy-to-use, and rewarding financial services. Operating in Nigeria, Ghana, Tanzania, Bangladesh, and Pakistan, PalmPay has been recognised by CNBC as one of the Top 300 Global Fintech Companies and ranked #2 overall and #1 in financial services on the Financial Times’ Africa’s Fastest Growing Companies 2025 list. Position Overview We are looking for a highly analytical Senior Collection Data Analyst to support our loan collection and recovery teams with data-driven insights. This role will be responsible for SQL-based data extraction, reporting automation, strategy analysis, KPI tracking, and performance optimization. The ideal candidate must have strong Excel skills, SQL knowledge, and experience building structured reporting systems. Key Responsibilities 1. SQL Data Extraction & Modeling Write complex SQL queries to extract, clean, and transform collection-related datasets. Build analytical data models for portfolio performance, delinquency behavior, and recovery trends. Ensure accuracy, consistency, and reliability of collection data sources. 2. Reporting System Development Build and maintain weekly, monthly, and quarterly recovery reports for management. Automate reporting dashboards and ensure structured, timely data delivery. Support regulatory and internal reporting requirements. 3. KPI & Strategy Effectiveness Analysis Define, track, and evaluate core KPIs such as repayment rate, roll-rate movement, bounce rates, and collector performance. Assess the effectiveness of collection strategies across buckets and channels (call center, field collection, digital reminders). 4. Recovery Curve & Efficiency Analysis Build and analyze recovery curves, first-payment default patterns, and loss forecasts. Evaluate collector and team efficiency, providing actionable recommendations to improve performance. 5. Data Visualization & BI Tools Build dashboards and visual reports using Excel (advanced), Power BI, or Google Data Studio. Present insights and trends clearly to leadership and operations teams. 6. Process Understanding & Optimization Gain deep understanding of collection workflows, SOPs, and operational pain points. Use data-driven insights to recommend improvements to strategies and processes. 7. Cross-Department Collaboration Collaborate with risk, collections, call center, and product teams to understand issues and develop solutions. Translate data insights into clear business actions and operational guidance. Requirements Bachelor’s degree in Statistics, Economics, Finance, Mathematics, Computer Science, or related field. 2–4 years of experience as a Data Analyst or Collection Analyst, Strong proficiency in Excel & SQL for data extraction and data analysis and reporting. Strong understanding of collection operations, loan lifecycle, and risk metrics is preferred. Excellent communication and problem-solving skills. Ability to work with cross-functional teams in a fast-paced environment. Compensation & Benefits Competitive salary Festival bonuses Mobile & internet allowance Career growth opportunities in a fast-scaling international fintech

Responsibilities

The Senior Collection Data Analyst will support loan collection and recovery teams by providing data-driven insights through SQL-based data extraction, reporting automation, and performance optimization. Key tasks include building analytical data models, developing reporting systems, and analyzing collection strategies.