About The Team
This role primarily supports SG SPayLater's Operations, including Collections, Quality Assurance (QA), and Customer Service (CS), through data-driven analysis and operational execution. Secondary focus is on supporting Product Management and Business Intelligence for product enhancements and performance monitoring.
Job Description
Operational Analytics & Daily Business Support (Primary)
- Conduct in-depth data analysis to support:
- SG SPayLater operations performance
- Collections strategy and effectiveness
- QA checks on processes and case handling
- Customer Service performance (e.g. SLAs, handling quality, pain points)
- Build and maintain reports and dashboards for:
- SPL Ops KPIs
- Collections metrics (e.g. DPD, cure rates, contact effectiveness)
- QA scoring and trend monitoring
- CS metrics (e.g. FCR, E2E, FRD, CSAT, complaint trends)
- Work closely with operations, collections, QA, and CS teams to:
- Identify issues, process gaps, and operational risks
- Provide actionable insights and recommendations to improve efficiency, quality, and customer experience
- Support ad-hoc investigations (e.g. spike in complaints, changes in delinquency, anomaly in operational metrics).
Operations Process & Quality Support (Primary)
- Support SOP and process change implementation for SPL Ops, Collections, QA, and CS.
- Participate in root cause analysis (RCA) for:
- Operational errors
- Escalated cases
- Repeated customer issues
- Assist in defining and tracking control checks and quality standards across key processes.
Product Management & BI Support (Secondary)
- Support Product Managers and Business teams with:
- Analysis on product features impact to ops, collections, QA, and CS
- Insights on customer behavior, repayment patterns, and product usage
- Perform UAT (User Acceptance Testing) on new features / enhancements:
- Validate business logic, credit/ops flows, notifications, and edge cases
- Ensure no negative impact to operations, collections, QA, or CS workflows
- Translate operational and customer pain points into requirements and feedback for product and system improvements.
Requirements
- Bachelor's Degree in Data Science, Business Analytics, Finance, Economics, Statistics, or related disciplines.
- Open to fresh graduates and candidates with up to 2 years of relevant experience.
- Strong data analytics skills, including: SQL, Python, Excel, Experience with BI / dashboard tools and big data environments is an advantage.
- Strong stakeholder communication skills, able to explain complex data and findings to non-technical operations and business teams (Ops, Collections, QA, CS, PM, etc.).
- Solid understanding of:
- Consumer lending / BNPL / credit products
- Collections processes and strategies
- Customer Service and QA operations
- Prior experience in:
- Financial services / fintech
- Operations analytics, risk analytics, or business operations roles.
