(Senior) Analyst, Operational Risk
Summary
Analyze operational signals, transaction flows, and behavioral data on Lalamove's logistics platform to detect fraud, account abuse, and financial crime using SQL and quantitative analytics.
At Lalamove, we believe in the power of community. Millions of drivers and customers use our technology every day to connect with one another and move things that matter. Delivery is what we do best and we ensure it is always fast and simple. Since 2013, we have tackled the logistics industry head on to find the most innovative solutions for the world’s delivery needs. We are full steam ahead to make Lalamove synonymous with delivery and on a mission to impact as many local communities as we can. We have massively scaled our efforts across Asia and now have our sights on taking our best in class technology to the rest of the world. And we need your help to get us there!
Reporting to the Senior Manager, Safety, you will be responsible for identifying, analyzing, and mitigating complex fraudulent and criminal activities across our ecosystem. You will leverage data analytics and behavioral intelligence to uncover vulnerabilities, build proactive risk indicators, and advise on proportional controls that safeguard our platform without unnecessarily disrupting supply and demand.
What you’ll do:
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Analyze platform-wide operational signals, transaction flows, and behavioral data to uncover fraud vectors, account abuse, and system vulnerabilities.
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Conduct qualitative and quantitative analysis on complex risk scenarios (e.g., account takeover, promo abuse, collusive ordering, financial crime).
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Gather, handle, and evaluate risk intelligence related to anti-narcotics and anti-money laundering (AML).
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Monitor risk patterns and trends to design friction-balanced enforcement strategies.
What you'll need:
Essential Qualifications:
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A recognized Bachelor's degree or above, preferably in Computer Science, Data Analytics or Logistics.
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At least 2 years of working experience in data analytics, fraud investigation, or case management. Fresh graduates with outstanding analytical skills will also be considered.
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Strong hands-on proficiency in SQL and quantitative analytics methods.
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Proficiency in both English and Chinese (written and spoken).
Preferred Qualifications:
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Prior experience in managing risk intelligence related to narcotics, cybercrime, or money laundering.
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Experience with data visualization tools (e.g. Tableau, PowerBI).
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