The Advance Analytics role is responsible for designing, developing, and delivering data analytics and artificial intelligence solutions that turn enterprise data into actionable insight and measurable business value. The role combines advanced analytics, machine learning, and generative AI capabilities to support data-driven decision making across business and operational functions, while ensuring all solutions are built responsibly and in compliance with applicable data governance and regulatory requirements (including BNM RMiT and PDPA). The incumbent works closely with business stakeholders and IT teams to identify high-impact use cases, translate them into analytical and AI models, and operationalize them on the enterprise data platform.
Main Duties & Responsibilities
- Engage business and operational stakeholders to identify, scope, and prioritise high-value analytics and AI use cases aligned to business objectives.
- Translate business questions into analytical requirements, data logic, KPIs, and measurable success criteria.
- Perform data sourcing, cleaning, validation, profiling, and exploratory data analysis to prepare datasets for analytics and AI modelling.
- Design, develop, train, and evaluate machine learning and statistical models (e.g. classification, regression, clustering, forecasting) to address business problems.
- Develop and deliver generative AI and large language model (LLM) solutions, including use cases such as document intelligence, summarisation, and retrieval-augmented generation (RAG).
- Build interactive dashboards, reports, and data visualisations using BI tools to communicate insights clearly to technical and non-technical audiences.
- Operationalise analytics and AI solutions on the enterprise data platform, supporting deployment, monitoring, and ongoing model performance management (MLOps).
- Document analytical logic, model assumptions, business definitions, data lineage, and reporting specifications to ensure transparency and reproducibility.
- Apply responsible AI principles, addressing model risk, bias, fairness, and explainability in line with internal governance and regulatory expectations.
- Ensure all analytics and AI solutions comply with data governance, data quality, and regulatory requirements including BNM RMiT, PDPA, and Shariah governance considerations where applicable. Collaborate with data engineering, data governance, IT security, and business teams to ensure solutions are scalable, secure, and well-governed.
- Continuously research and evaluate emerging analytics and AI tools, techniques, and platforms to strengthen the organisation's data and AI capability.
Requirement
- Bachelor's degree in Data Science, Computer Science, Statistics, Mathematics, Actuarial
- Science, Information Technology, or a related quantitative discipline. A Master's degree or relevant professional certification in data science, machine learning, or artificial intelligence is an advantage.
- Minimum 8 to 10 years of relevant experience in data analytics, data science, machine learning, or AI solution delivery, preferably within financial services, insurance, or Takaful.
- Hands-on experience developing analytics, statistical, and machine learning models and deploying them into production environments.
- Practical experience with BI and data visualisation tools, SQL, and a programming language commonly used for analytics and AI such as Python.
- Exposure to cloud-based analytics and AI platforms (e.g. Microsoft Azure) and to modern data platform architectures is an advantage.
- Experience working within a regulated environment, with familiarity in data governance, risk management, and compliance practices, is preferred.
