Assistant Vice President - Treasury Middle Office (Analytics)

About the role

This role sits in the Treasury Middle Office and focuses on data analytics and management information. It covers collecting and analysing Treasury data, building dashboards and reports, automating reporting, ensuring data quality, and supporting Treasury management decisions.

Key responsibilities

• Collect, organise and analyse Treasury data from systems, reports and data sources.
• Develop dashboards and management reports on liquidity, funding, deposit movements, FX positions and transactions, money market activity, customer trends and other indicators.
• Produce daily, weekly, monthly and ad-hoc analytical reports and present findings clearly.
• Build and maintain automated reports and dashboards using Python, Excel, Power BI or similar tools, and automate repetitive manual processes.
• Validate and reconcile data, identify missing or inconsistent records, and coordinate with departments to resolve data-quality issues.
• Document calculation logic, assumptions and data definitions, and keep version control and backups of analytical tools.
• Identify opportunities to use AI and automation, while respecting data confidentiality and security.
• Work with IT and other departments on system access, databases and technical support.
• Support ad-hoc analysis, scenario analysis, trend analysis, management presentations and business planning, and help build a data-driven culture in Treasury.

Required profile

• Bachelor's degree in Finance, Accounting, Economics, Business, Data Analytics, Statistics, Computer Science or a related field; a Master's degree is an advantage.
• At least 5 years of experience in financial analysis, management reporting, data analytics, business intelligence or report automation.
• Good analytical and problem-solving skills with strong attention to data accuracy.
• Ability to explain analytical findings to technical and non-technical users.
• Proficiency in written and spoken English and Myanmar.

Required skills

• Good knowledge of Microsoft Excel, including formulas, PivotTables, data analysis and reporting.
• Basic practical knowledge of Python for data processing and report automation; familiarity with Pandas and OpenPyXL is an advantage.
• Experience with dashboard development or business intelligence tools such as Power BI is an advantage.
• Understanding of databases, structured data and data relationships, and of banking and financial data.