You will be responsible for leading the end-to-end delivery of data and analytics solutions across the organisation, spanning business intelligence (BI), reporting, dashboards, data modeling, and AI/ML use cases. You will analyse complex business problems, translate requirements into technical specifications, and ensure high-quality, scalable analytics solutions that support strategic and operational decision-making.
You will serve as a trusted analytics partner to business units, providing advisory on data-driven improvements, championing best practices, and supporting the organisation’s transformation toward a fully insight-driven and AI-enabled enterprise. You will also play a key role in fostering data culture, supporting data literacy, and enabling the organisation’s transformation into an insight-driven enterprise.
JOB SCOPE
- Lead requirements gathering for advanced analytics initiatives, including reporting, dashboards, data modeling, and AI/ML use cases.
- Analyse business processes to identify improvement opportunities and propose data-enabled solutions.
- Evaluate and recommend suitable analytics and AI/ML use cases aligned with organisational priorities and feasibility.
- Translate complex business needs into clear functional specifications, user stories, data requirements, and acceptance criteria.
- Partner with BI developers to design enterprise dashboards, KPIs, and decision-support tools that drive measurable outcomes.
- Collaborate with data scientists on predictive modeling and AI/ML initiatives, including business framing, feature requirements, validation, and success metrics.
- Work closely with data engineers to ensure data pipelines, data models, and integration workflows support analytics and AI operations.
- Oversee UAT and validate outputs of reports, dashboards, and models to ensure accuracy, quality, and business alignment.
- Support the operationalisation of AI/ML models into dashboards, workflows, or enterprise systems.
- Develop adoption, training, and change management plans to ensure successful implementation and user uptake of analytics and AI solutions.
- Produce comprehensive documentation including business cases, requirements, data dictionaries, process maps, and impact assessments.
- Ensure that all analytics and AI/ML solutions comply with data governance, cybersecurity, privacy, and responsible AI standards.
- Mentor junior analysts and contribute to building analytics capability across the organisation.
- Stay abreast of trends in BI, analytics, and AI/ML to guide continuous improvement and innovation.
REQUIRED COMPETENCIES
- Strong expertise in end-to-end analytics delivery, covering descriptive, diagnostic, predictive, and AI/ML-based solutions.
- Ability to translate complex data concepts, model outputs, and technical details into clear business insights and recommendations.
- Strong command of BI tools (Power BI, MicroStrategy) and proven ability to design impactful dashboards and KPI frameworks.
- Solid understanding of data modeling concepts, ETL/ELT processes, and data lifecycle management.
- Familiar with AI/ML concepts (e.g., predictive modelling, feature engineering, model evaluation) and able to work closely with data scientists.
- Skilled in leading requirement workshops, stakeholder discussions, and cross-functional analytics projects.
- Strong analytical thinking, structured problem solving, and root-cause analysis capabilities.
- Excellent communication, influencing, and stakeholder management skills across varying seniority levels.
- Demonstrates leadership qualities, with the ability to mentor team members and drive best practices in analytics delivery.
- Commitment to responsible data use, data governance, and ethical application of AI/ML technologies.
QUALIFICATIONS
- Bachelor’s degree in Data Science, Computer Science, Statistics, Information Systems, or equivalent from accredited institutions.
- 7–10 years of experience in business analysis, BI, data analytics, or related areas.
- Proven experience delivering enterprise dashboards, complex reporting requirements, and analytics solutions.
- Exposure to AI/ML projects, including business problem framing and interpreting model outputs.
- Good understanding of SQL; familiarity with Python or analytics tools is an added advantage.
- Experience working in large enterprise, public sector, or regulated environments is preferred.