Tuyển dụng Senior Collection Analytics & Modeling Executive tại Hồ Chí Minh

About the Role:

We are looking for a data-driven professional to develop and optimize analytical models and collection strategies that improve debt recovery performance at SFinance.

This role combines predictive modeling, customer segmentation, collection strategy analytics, and performance monitoring to support data-driven decision-making, improve collection effectiveness, and optimize operational costs.

Key Responsibilities

1. Collection Modeling & Predictive Analytics

• Develop and optimize predictive models to assess customers’ payment behavior, recovery probability, and collection outcomes.
• Build collection scoring models and predictive models for Promise-to-Pay (PTP), Roll Forward, Cure Probability, and Recovery Forecast.
• Monitor model performance and recommend improvements based on actual collection results.

2. Collection Strategy & Customer Segmentation

• Analyze customer behavior and repayment patterns across delinquency buckets.
• Develop customer segmentation and recommend tailored collection strategies across call, SMS, digital, and field collection channels.
• Conduct Champion-Challenger testing to evaluate and optimize collection strategies.
• Identify opportunities to improve collection effectiveness and resource allocation through data-driven insights.

3. Data Analytics & Business Intelligence

• Extract and analyze data from the Data Warehouse to support collection strategy development and operational decisions.
• Develop dashboards and reports to monitor key performance indicators, including Collection Rate, Cure Rate, Roll Rate, Recovery Rate, RPC Rate, and PTP Fulfillment Rate.
• Automate recurring reports and improve the efficiency of collection performance monitoring.

4. Model Monitoring & Optimization

• Monitor model accuracy, stability, and effectiveness after implementation.
• Perform model validation, recalibration, back-testing, and stress-testing where appropriate.
• Identify model performance gaps and recommend corrective actions to maintain model reliability.

5. Cross-functional Collaboration

• Work closely with Collection Operations, Risk Management, Data Engineering, IT, and Digital Transformation teams to implement analytical solutions.
• Translate business requirements into analytical models and actionable recommendations.
• Participate in AI/ML initiatives to enhance collection strategies and operational efficiency.

Yêu cầu công việc

Education & Experience:

• Bachelor's degree or above in Statistics, Data Science, Mathematics, Computer Science, Econometrics, Finance, Banking, or related fields.
• 3–7 years of relevant experience in Collection Analytics, Credit Risk Modeling, Data Science, or Banking/Consumer Finance Analytics.
• Experience in consumer finance, banking, or debt collection analytics is highly preferred.

Technical Skills:

• Strong SQL skills for data extraction and analysis.
• Proficiency in Python or SAS for statistical analysis and model development.
• Experience with Power BI, Tableau, or other data visualization tools.
• Strong knowledge of statistical modeling, predictive analytics, and model performance evaluation.
• Knowledge of Machine Learning, Hadoop/Spark, Cloud Analytics, or IFRS 9 modeling is an advantage.

Core Competencies

• Strong analytical and quantitative problem-solving skills.
• Ability to translate complex data into actionable business insights.
• Strong business understanding of collection operations and debt recovery strategies.
• Good communication and cross-functional collaboration skills.
• Proactive, detail-oriented, and results-driven mindset.

Quyền lợi

• Thưởng: Receive a competitive compensation package with regular salary reviews, with total income reaching up to 14 months’ salary per year.
• Chăm sóc sức khoẻ: Be covered by a comprehensive health insurance plan.
• Nghỉ phép có lương: Enjoy a competitive annual leave package, including 1 fully paid birthday leave.
• Đào tạo: Enhance your capabilities through training programs, learning support, language development, and knowledge-sharing activities.
• Cơ hội du lịch: Take part in annual company trips
• Hoạt động nhóm: team-building activities.
• Khác: Work alongside friendly and supportive colleagues who value individual growth and development. Enjoy a Monday–Friday work schedule (40 hours/week) with a 1.5-hour lunch break. Experience a modern, open workspace equipped with all the tools and resour