[DGDD] Manager/Senior Manager, Data Analytics, Digital Governance & Data Dept

• Transform raw data into meaningful insights through advanced statistical analysis, predictive modelling, and machine learning techniques. Develop and maintain analytical models to support forecasting, segmentation, and optimisation initiatives across various business functions. • Partner with stakeholders to understand business requirements and translate them into analytical solutions. Create comprehensive reports and presentations that communicate complex findings to both technical and non-technical audiences, ensuring insights drive actionable business decisions. • Collaborate with data engineering teams to ensure data quality, accessibility, and governance standards. Design and implement data collection strategies, establish key performance indicators, and maintain data documentation to support reproducible analysis. • Work closely with product managers, business users, and senior leadership to identify opportunities for data-driven improvements. Lead analytical projects from conception to implementation, managing timelines and deliverables whilst ensuring alignment with organisational priorities. • Design data analytics strategies to achieve the data transformation objectives and desired outcomes, which include the alignment with WOG directions and initiatives. • Create and maintain a short to mid-term data analytics roadmap with business unit that sets out the deliverables and milestones to achieve the desired outcomes. • Drive the adoption of data analytics and build data analytics competencies and capabilities for officers in ACRA.

• Professional Qualification in Data Science, Statistics, Mathematics, Computer Science, Information Systems, Economics or related quantitative field. • Experience in data science or analytics roles with proficiency in Python or R, SQL, and statistical analysis. Demonstrated experience with machine learning frameworks, data visualisation tools such as Tableau or Power BI, and cloud platforms including AWS, Azure, or Google Cloud. • Strong foundation in statistics, hypothesis testing, and experimental design. Experience with supervised and unsupervised learning techniques, time series analysis, and A/B testing methodologies. Ability to work with large, complex datasets and handle missing or incomplete data effectively. • Experience with deep learning frameworks, natural language processing, or specialised domain knowledge relevant to our industry. Previous experience with agile development environments. • Hands-on experience in system implementation and vendor management in medium scale projects, preferably in finance or accounting industry. • Proven track record of translating business problems into analytical frameworks and delivering insights that drive measurable impact. Experience presenting findings to senior stakeholders and influencing strategic decisions through data-driven recommendations. • Proven ability to adjust quickly to shifting priorities, multiple demands, ambiguity and rapid change. • Natural curiosity and self-directed ability to seek out information and meet goals/deadlines.