Krungsri Bank
Data Analytics Consultant (Mule & Fraud Analytics)
Builds and runs a day-to-day mule-account and fraud analytics capability at Krungsri Bank: analyzing customer, transaction, and device data to uncover mule patterns and networks, developing and back-testing detection logic, and presenting insights to management. Core stack: SQL, Python/R, BI tools (Tableau/Power BI/Qlik), and AI/ML techniques.
- Compensation
- Not disclosed
- Location
- Yan Nawa, Bangkok
- Work setup
- Hybrid
- Seniority
- Not specified
- Employment
- Not specified
- Experience
- 5+ years
- Category
- Data analytics
- Posted
Skills
Must have
- 5+ years in Data Science, Advanced Analytics, Fraud Analytics, Financial Crime Analytics, Risk Analytics, or Transaction Monitoring Analytics
- Data analysis & visualization with Tableau, Power BI, Qlik, or other BI tools
- Advanced SQL and Python / R
- Statistics, pattern and network analysis
- Able to apply AI / ML for analytical use cases
- Ability to use GenAI tools responsibly
Nice to have
- Experience in mule-account, fraud, or financial-crime analytics
- Data science background
Full description
Role overview
- Build a dedicated day-to-day mule analytics capability to identify emerging patterns, connected networks, and risk exposure.
- Assess mule trends and control effectiveness using internal and relevant external data.
- Develop and validate analytical detection strategies, indicators, thresholds, and use cases.
- Turn complex analysis into actionable insights and decision support for management committees.
What you'll do
- •Analyze customer, account, transaction, device, channel, and other relevant data to uncover mule patterns, anomalies, and connected networks.
- Quantify risk exposure and assess the effectiveness of existing mule-detection and prevention controls.
- Develop and back-test detection logic, indicators, thresholds, segmentation, and analytical use cases.
- Prepare recurring and ad hoc mule analytics reports/support to management committees.
- Engage directly with business, fraud, risk, and operational stakeholders to discuss findings, challenge assumptions, debate options, and translate analytics into practical decisions.
- Clearly communicate methodology, limitations, and recommendations, while maintaining reusable analytical documentation for consistency and knowledge transfer.
Apply now if you have these advantages
- 5+ years in Data Science, Advanced Analytics, Fraud Analytics, Financial Crime Analytics, Risk Analytics, or Transaction Monitoring Analytics.
- Experience in mule-account, fraud, or financial-crime analytics is preferred.
- Data science background is preferred.
- Data Analysis & Visualization – Experience with Tableau, Power BI, Qlik, or other BI tools.
- Advanced SQL and Python / R
- Statistics, pattern and network analysis
- Able to apply AI / ML for analytical use cases
- Ability to use GenAI tools responsiblyWhy join Krungsri?
- As a part of MUFG (Mitsubishi UFJ Financial Group), we are truly a global bank with networks all over the world.
- We offer a striking work-life balance culture with hybrid work policies (3 days in office per week).
- Unbelievable benefits such as attractive bonuses, employee loan with special rates and many more.
Apply now before this role is close.