Collaborate with cross-functional teams to improve reporting processes and automate manual workflows
Build proof-of-concepts (POCs) for LLM-powered tools or agents to support workflow efficiency — report generation, data interpretation, or process automation
Experiment with prompt design, tool integration, and basic agent workflows to enhance productivity use cases
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Insights Generation - Analyze campaign performance, audience data, and digital channels to generate actionable insights that inform marketing strategies, targeting, and media optimization efforts.
Proposal and Report Building - Collaborate with cross-functional teams to develop data-driven proposals, presentations, and reports for internal stakeholders/clients.
SQL and Python Data Manipulation - Write and optimize SQL queries to extract data from BigQuery, apply Python to automate workflows and conduct advanced analytics.
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Analyze alert patterns to identify refinements (what to add, change, or remove) in test logic.
Connect data across systems/platforms to detect duplicate pathways or leakages and validate hypotheses.
Draft queries and use productivity AI tools to accelerate exploration, documentation, and summaries; partner with PADI when deeper engineering or data‑science support is required.
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Attend and assist in facilitating project meetings / workshops with client stakeholders.
Propose, implement, and validate data science models, ensuring functional and non-functional requirements such as explainability, fairness, scalability, security, integration and operational costs.
Participate actively in software development processes and best practices, documentation of requirements and software codes during the software development lifecycle.
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Lead and formulate the solution and platform stack through understanding of the business needs of various Programmes and Maintenance Systems managed under Intelligence Analytics System & Anti Scam, and other Intel units in the Home Team.
Work closely with Head Intelligence Analytics Systems and Head Anti-Scam to develop solutions to meet requirements. Provide support at the various stages in the ICT Development lifecycle (AOR, AOB, Procurement and Delivery).
Define and maintain technical standards and best practices for Intelligence Analytics projects across HTDs, taking into consideration the operational concerns and constraints faced by Intel units and the data and analytics needs.
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