Business Intelligence / Data Scientist

Work closely with other business intelligence and data teams to build datasets serving the purpose of treasury and risk management.

Responsible for the architecture design and core module development of LLM-based AI Agent systems, including task planning, memory management, tool invocation, and workflow execution;

Leverage key technologies such as LLMs, RAG, vector search, and function calling to build intelligent systems with contextual understanding and knowledge injection capabilities;

Drive the application of AI Agents in vertical scenarios such as search, trading, deep analysis, and automated data engineering to unlock the full value of LLMs.

Develop and maintain sophisticated risk management systems, dashboards and automated reports to help the team meet its management objectives and regulatory requirements.

Analyze and interpret large (PB-scale) volumes of transactional, operational, customer and financial data using proprietary and open source data tools, platforms and analytical tool kits.

Translate complex findings into simple visualisations and recommendations for execution by operational teams and executives.

Work across all aspects of data from engineering to building sophisticated visualisations, machine learning models and experiments.

Be part of a fast-paced industry and organisation where time to market is critical.

Develop and maintain sophisticated risk management systems and dashboards to monitor limits, detect breaches, and support timely risk mitigation

Degree in a quantitative discipline, such as Mathematics/Statistics, Actuarial Sciences, Computer Science, Engineering, or Life Sciences

3-5 years of full-time work experience in an Analytics or Data Science role

A self-driven team player with the ability to quickly learn and apply new tools and techniques such as proprietary analytical software, data models and programming languages

A natural curiosity to identify, investigate and explain trends and patterns in data and an ability to analyse and break down complex concepts and technical findings into clear and simple language for communication

Prior internal/client-facing consulting/business transformation experience preferred.

A passion for Emerging Technologies related to Blockchain, Machine Learning and AI

Competency in two or more of the following:

An analytical software (e.g. R, SAS)

A data visualisation tool (e.g. Qlikview, Tableau, PowerBI,)

A relational or graph database management tool (e.g. SQL, NoSQL, Neo4J)

Programming (e.g. VBA, C++, Java, Python)