- Leverage LLM and GenAI to develop, optimize, and maintain advanced solutions to support internal audit activities.
- Analyse heterogeneous and unstructured data and generate actionable insights to enhance risk and control activities.
- Develop custom data pipelines and machine learning models to analyse structured and unstructured data, and generate actionable insights to enhance risk and control activities.
- Work on Big Data infrastructure such as Snowflake and OpenSearch to efficiently manage data on very large datasets.
- Work closely with business stakeholders to analyse large data sets, trends and results to drive data-driven operational risk decisions.
- Collaborate with an existing internal community of data scientists to solve complex problems and influence change.
- Keep abreast of technique development in data analytics and recommend adoption of best practices into GIC.
What qualifications or skills should you possess in this role
- Bachelor's degree in Computer Science, Information Systems, or relevant quantitative fields.
- At least 5 years (AVP) and 10 years (VP)of experience in data science or data engineering.
- Highly proficient in Python and working experience with Python based data workflows.
- Experience in processing data in SQL databases and big data platforms, able to manipulate data sets and build end-to-end process from ETL.
- Good understanding with machine learning algorithms, statistical models and other common machine learning techniques.
- Good understanding about large language model (LLM), such as prompt engineering, agentic LLM, model serving and finetuning.
- Knowledge of dashboard creation and visualisation using Streamlit will be an added advantage.
- Strong analytical and organization skills, with the ability to collect, organise, analyse, and disseminate significant amounts of information with attention to detail and accuracy.
- Self-motivated and driven, able to work independently on technical projects and be a team player.
