Associate Director, Enterprise Analytics (Data Science)

Roles and Responsibilities

• Guide a team of 5 onshore and 2 offshore data scientists, as the Data Science Functional Lead, to deliver the analytics roadmap for AIA Singapore.
• Take overall responsibility of the data science workplan in terms of selecting the right advanced statistical techniques and machine learning models.
• Be responsible for creating best modelling, coding and measurement practices to ensure efficient and quality delivery of work from the data science team.
• Implement analytical models into production systems by collaborating with relevant stakeholders and be responsible for their long-term maintenance and continuous improvement.
• Develop processes and tools to monitor and analyse model performance, as well as implement improvements as needed.
• Communicate findings from analytical modelling results to relevant stakeholders that will give insights to improve decision making and drive business performance.
• Develop in depth understanding of the business and be able to advise the business on the right data science approach by participating in business discussions and presentations as applicable.
• Work together with Head of Analytics to further develop the long-term analytics roadmap and strategy for AIA Singapore.

Requirements

• Bachelor’s degree holder, ideally in STEM disciplines (Science, Technology, Engineering, Math); graduate degree in Statistics, Applied Math, Data Science or another related quantitative field is preferred.
• Approximately 5-10 years of working experience in data science. 2-3 years’ experience in managing or mentoring a data science team would be preferable.
• Experience using programming languages (e.g. Python, R, SQL) to manipulate data and draw insights from large data sets.
• Experience with business intelligence tools (e.g. Tableau), Excel, PowerPoint.
• Knowledge of a variety of machine learning techniques (clustering, decision tree, random forest, artificial neural networks, etc.) and their real-world advantages/drawbacks.
• Knowledge of advanced statistical techniques and concepts (regression, properties of distributions, statistical tests and proper usage, etc.) and experience with applications.
• Experience in ideating, building, testing, production deployment and maintenance of Machine Learning algorithms.
• Experience in creation of best practice standards and guidelines for modelling, coding or measurement techniques for data science teams.
• Experience of working on Azure based cloud technologies will be highly desirable.
• Experience in SPARK based technologies is highly desirable.
• Experience of working in either Banking, Insurance or Healthcare sectors is highly desirable.
• Strong analytical skills, deductive reasoning, problem solving and critical thinking skills.
• Excellent relationship management, strong team building, and the ability to work across business units and functions to drive positive business outcomes.
• Project management skills and ability to manage multiple priorities.
• Strong sense of urgency and accountability to drive business outcomes.
• Passionate about working with numbers.
• A drive to learn and master new technologies and techniques.

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