Responsible for changing AIA’s analytics landscape by delivering best-in-class advanced data science solutions to drive business growth, improve efficiencies and reduce costs.
Roles and Responsibilities:
· Design, implement and evaluate advanced statistical and machine learning models and approaches for application to various business problem statements.
· Communicate findings from analytical modelling results to relevant stakeholders that will give insights to improve decision making and drive business performance.
· Implement machine learning models into production systems through proper MLOps practices and collaborating with relevant stakeholders.
· Develop processes and tools to monitor & analyse model performance, incorporate Responsible & Explainable AI for both traditional and Generative AI and implement improvements as needed.
· Provide support in building the foundation of technical analytics capabilities within Enterprise Analytics department, including sharing of best practices for coding, modelling, and analysis within the team.
· Drive analytics innovation by keeping abreast of industry’s trends, evaluating, and adapting new and improved data science approaches for the business.
· Develop in depth understanding of the business and be able to advise the business on the technical solutioning by participating in business discussions and presentations as applicable.
Financial and Non-Financial Measures:
· Quality and Timeliness of completion of deliverables
· Effective stakeholder management
· Achieve planned benefits realisation
· Effective problem solving through self or through collaboration with teams
Communication Requirements
· Able to communicate to all levels in the organisation.
· Able to communicate complex model results in a simplified, comprehensible, and convincing manner for non-technical stakeholder audiences through Data & Business Storytelling skills.
Minimum Job Requirements:
· Bachelor’s degree ideally in STEM disciplines (Science, Technology, Engineering, Math); graduate degree in Economics, Statistics, Applied Math, Data Science, or another related quantitative field is preferred.
· Approximately 4-6 years of relevant hands-on experience in analytics/data science.
· Experience in Python for data analysis, visualization, and insight generation.
· Experience handling large datasets using advanced SQL/Spark based Big-Data technologies. Knowledge of Databricks is a plus.
· Experience with Business Intelligence tools (e.g. Tableau), Excel, PowerPoint.
· Knowledge of advanced statistical inferencing concepts (Distributions, Regressions, Hypothesis Testing, ANOVA, PCA, Factor Analysis, Feature Selection etc.) and experience with their appropriate applications.
· Knowledge of a variety of machine learning methods (GLMs, Clustering, Decision Trees, Ensemble Models, Time Series etc.) and their real-world advantages/drawbacks.
· Experience in maintaining Machine Learning production systems and MLOps.
· Understanding and experience in implementation of LLM based RAG applications will be a plus.
· 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, accountability, and ownership to drive business outcomes.
· Passionate about working with numbers.
· A drive to learn and master new technologies and techniques.
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