Chưa ghi lương
Ho Chi Minh City
Phân tích dữ liệu tín dụng cho sản phẩm BNPL và vay tiền mặt tại Zalopay, hỗ trợ quyết định cho vay và giám sát rủi ro danh mục.
Tóm tắt bằng AI từ JD gốc, đọc JD gốc trước khi ứng tuyển.
About the team Zalopay's Underwriting team owns credit decisions end-to-end for BNPL and cash loan products serving millions of users, in partnership with leading banks and consumer finance companies — from a user's first visit through submission, approval, disbursement, and repayment. We decide who gets offered credit, monitor how the portfolio performs, and build the data that proves whether we were right.
What you'll do Monitor the portfolio: build and maintain the reports and dashboards that track the health of our lending book — approval rates, funnel conversion, delinquency by cohort.
Investigate: when a number moves and nobody knows why, you're the detective — deep-dive the data, separate real risk changes from mix shifts and data artifacts, and land on the root cause.
Own the data foundation: keep our core data assets — the end-to-end lending funnel and portfolio labels — correct, reconcilable, and trusted; chase reliability issues in partner data and drive the fixes.
Shape underwriting strategy: turn your analysis into recommendations for whitelist expansion and the refinement of our underwriting rules.
Collaborate on models and policy: analyze credit model performance with our data scientists and review new lending policies, pointing out flaws and opportunities before they go live.
Communicate: translate your findings into clear, actionable insights for the business, product, engineering, and data science teams you work with daily.
Must-have Technical Skills: Strong SQL and working Python; expected depth scales with level.
Analytical & Problem-Solving Mindset: You can break down ambiguous problems, form hypotheses, and use data to find the root cause — validating the data before trusting it.
Proficient English Skills: Above-average English proficiency, equivalent to an IELTS score of 6.5 or higher.
Nice-to-have Consumer lending / credit risk analytics: funnel and approval analytics, DPD/MOB cohorts, vintage and roll-rate analysis. Credit model validation and backtesting. E-wallet, fintech, or payments background. Dashboarding (Tableau, Power BI, Looker) and pipeline tooling (Airflow, ETL).
Đang tải…
Nguồn: careers Zalopay
VNG fintech — payments & lending
HCMC · Sync · 22 job
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Thành phố Hồ Chí Minh | Thành phố Hồ Chí Minh | ||
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Thành phố Hồ Chí Minh | Thành phố Hồ Chí Minh | ||
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Thành phố Hồ Chí Minh | Thành phố Hồ Chí Minh | ||
Thành phố Hồ Chí Minh | Thành phố Hồ Chí Minh | ||
Thành phố Hồ Chí Minh | Thành phố Hồ Chí Minh | ||
Thành phố Hồ Chí Minh | Thành phố Hồ Chí Minh | ||
Thành phố Hồ Chí Minh | Thành phố Hồ Chí Minh | ||
Thành phố Hồ Chí Minh | Thành phố Hồ Chí Minh | ||
Thành phố Hồ Chí Minh | Thành phố Hồ Chí Minh | ||
Thành phố Hồ Chí Minh | Thành phố Hồ Chí Minh | ||
Thành phố Hồ Chí Minh | Thành phố Hồ Chí Minh | ||
Thành phố Hồ Chí Minh | Thành phố Hồ Chí Minh | ||
Thành phố Hồ Chí Minh | Thành phố Hồ Chí Minh | ||
Thành phố Hồ Chí Minh | Thành phố Hồ Chí Minh | ||
Thành phố Hồ Chí Minh | Thành phố Hồ Chí Minh | ||
Thành phố Hồ Chí Minh | Thành phố Hồ Chí Minh | ||
Thành phố Hồ Chí Minh | Thành phố Hồ Chí Minh |
22 job
22 job
Chưa ghi lương
Ho Chi Minh City
Phân tích dữ liệu tín dụng cho sản phẩm BNPL và vay tiền mặt tại Zalopay, hỗ trợ quyết định cho vay và giám sát rủi ro danh mục.
Tóm tắt bằng AI từ JD gốc, đọc JD gốc trước khi ứng tuyển.
About the team Zalopay's Underwriting team owns credit decisions end-to-end for BNPL and cash loan products serving millions of users, in partnership with leading banks and consumer finance companies — from a user's first visit through submission, approval, disbursement, and repayment. We decide who gets offered credit, monitor how the portfolio performs, and build the data that proves whether we were right.
What you'll do Monitor the portfolio: build and maintain the reports and dashboards that track the health of our lending book — approval rates, funnel conversion, delinquency by cohort.
Investigate: when a number moves and nobody knows why, you're the detective — deep-dive the data, separate real risk changes from mix shifts and data artifacts, and land on the root cause.
Own the data foundation: keep our core data assets — the end-to-end lending funnel and portfolio labels — correct, reconcilable, and trusted; chase reliability issues in partner data and drive the fixes.
Shape underwriting strategy: turn your analysis into recommendations for whitelist expansion and the refinement of our underwriting rules.
Collaborate on models and policy: analyze credit model performance with our data scientists and review new lending policies, pointing out flaws and opportunities before they go live.
Communicate: translate your findings into clear, actionable insights for the business, product, engineering, and data science teams you work with daily.
Must-have Technical Skills: Strong SQL and working Python; expected depth scales with level.
Analytical & Problem-Solving Mindset: You can break down ambiguous problems, form hypotheses, and use data to find the root cause — validating the data before trusting it.
Proficient English Skills: Above-average English proficiency, equivalent to an IELTS score of 6.5 or higher.
Nice-to-have Consumer lending / credit risk analytics: funnel and approval analytics, DPD/MOB cohorts, vintage and roll-rate analysis. Credit model validation and backtesting. E-wallet, fintech, or payments background. Dashboarding (Tableau, Power BI, Looker) and pipeline tooling (Airflow, ETL).
Đang tải…
Nguồn: careers Zalopay