Senior Assistant Director/ Assistant Director, Data Analytics

• Advanced quantitative analytics and modelling, and programme evaluation work.
  • Ensure that the findings made and insights drawn are based on sound, rigorous, and defensible methods so as to best inform policy and operations planning at AIC.
• Business intelligence and data operation initiatives.
  • Ensure the delivery of high-quality end to end analytics solution such as deep-dive data analysis, and timely provision of accurate information to AIC colleagues and external stakeholders.
  • Supervise data analytic projects that promote the adoption of a data-driven approach for service and operation planning, policy review, and collaboration with community partners

• Build and maintain effective working relationships with key internal stakeholders and external partners (including academic partners, visiting consultants, community care organizations, MOH, and NCSS) to understand big picture directions and to influence partners in the areas of advanced analytics and programme evaluation.
• Support the statistical analyses for major programme evaluations helmed by AIC and primary research projects.
• Inform planning and operational decision-making in the following ways:

Programme evaluations

• • Engage programme managers from divisions across AIC to understand programme intent and business needs.
  • Guide and facilitate the development of cogent theories of change and logic models that would inform choice of outcome indicators, study design, sample size calculations, and analytic plan.
  • Provide input in data collection methodology.
  • Conduct or supervise the conduct of data analysis to produce findings at the end of evaluation. Familiarity with analytic strategies for overcoming identification and small sample problems is desirable.
  • Produce or supervise the production of write-up that summarises evaluation methodology, findings, and conclusions to augment programme managers interim and final reports.

Business intelligence

• • Engage internal stakeholders from divisions across AIC to understand operational intents and business needs.
  • Develop and supervise the development of regular and ad-hoc data products, including, but not limited to, dataset extraction, dashboard creation, interactive geospatial map creation, infographics, and analyses based on machine learning methods.
  • Manage workload and turnaround time demands in a way that remains fair to team members while meeting operational requirements.
• Supervise the computation of relevant descriptive statistics, correlations, projections, and other insights to challenge assumptions, and confirm hypothetical relationships that are the basis of proposed programmes and other initiatives.
• Build advanced analytic capabilities among team members and across AIC divisions by conducting learning workshops, and co-conduct communities of practice. The goal is to help colleagues and Community Care partners become savvy and critical consumers of quantitative findings.
• Serve as consultant and advisor to other AIC divisions where programme evaluation has been outsourced to a third party. In this role, the SAD may be engaged to support the procurement process by:
  • reviewing and providing inputs to requirement specifications,
  • sitting on evaluation committees to help assess the quality of proposals received, and
  • reviewing and providing inputs to the interim and final reports.
• Help translate statistical and scientific language into layman terms to help colleagues interpret relevant research findings.

Job Requirements

• Degree in Data Science, Business Analytics, Statistics, Mathematics, or a related field with at least 10 years of relevant experience in providing data support to business units preferably in health or social care settings and 4 years of supervisory management experience.
• Business-oriented and the ability to deliver quality service in a fast-paced working environment.
• Proficient in data analysis software such as Python, Stata or R programming;
• Proficient in data visualisation tools such as Tableau or Power BI.
• Good knowledge of statistics and quantitative methods;
• Able to perform and complete stretch tasks under tight deadlines;
• Self-motivated, takes initiative, and able to manage multiple projects efficiently;
• Able to handle uncertainty and ambiguity and conduct analysis bearing in mind business objectives;
• Attentive to detail and committed to data accuracy;
• Flexible, self-motivated, and able to manage multiple projects efficiently.