The Advanced Analytics team is responsible for utilising mathematics and machine learning methodologies to solve business problems, explore new opportunities and generate insights in collaboration with business units. Team members are data scientists of varying experience with knowledge in one or more domain areas of data science, all of whom have a passion for using empirical research to solve complex problems and an ability to translate analytical insights into actionable recommendations for the business.
The main responsibilities include:
- Champion the use of advanced analytics across the organisation through knowledge sharing and socialisation of advanced analytics techniques;
- Adopt an iterative approach to initiatives, developing prototype solutions in Proof of Concepts (POCs) to test hypotheses, and embracing a fail-fast experimentation approach to solving complex problems;
- Develop predictive models using Generalised Linear Models, Markov chains and other advanced algorithms such as decision trees, random forests and neural networks;
- Utlise mathematical, statistical and machine learning techniques to solve business problems, explore new opportunities and generate insights from data;
- Become AWS Cloud Solution Architect certified and take responsibility for progressing the advanced analytics platform on AWS;
- Deployment of real-time statistical models and machine learning algorithms into a production operational environment using containerization;
- Leverage business and data knowledge to proactively pitch and discuss new ideas for generating data-driven insights with stakeholders and team members;
- Involvement in all phases of the solution lifecycle including ideation, problem formulation, analysis, feature selection, model development, testing, documentation, deployment, presentation and story-telling of results and translation of insights into actionable recommendations for the business;
- Communicate regularly and effectively with stakeholders throughout the entire solution lifecycle;
- Ensure all development follows the established advanced analytics standards, including Software Development Lifecycle (SDLC), model governance policies and audit requirements;
- Adhere to the compliance obligations relevant to the position; perform duties in an ethical, lawful and safe manner; undertake training as directed by the Compliance Leader; report and escalate compliance concerns, issues and failures; and disclose potential conflicts of interest.
Most Frequent Contacts
The Advanced Analytics team is an enterprise function, providing mathematical and machine learning expertise to solve business problems collaboratively with the following business units:
- Finance & Actuarial;
- Information Technology (IT);
This role will communicate regularly with stakeholders from these business units throughout initiatives and proactively engage in discussions to pitch new ideas for insights.
Qualifications – Required
- Degree in Data Science/Mathematics/Statistics or equivalent;
- 3+ years in a data science role using at least one analytical software such as R, Python or SAS;
- Passion for using mathematics to solve complex business problems;
- Knowledge of foundational statistical analysis such as sampling, distributions, feature selection techniques and significance testing;
- Experience in a previous role of fitting at least one of Generalied Linear Models (GLMs), decision trees, random forests or neural networks;
- Ability to manipulate and analyse complex, high volume, high dimensionality data from varying sources;
- Excellent communication and stakeholder management skills;
- Clear report writing and presentation skills with an ability to communicate complex ideas in a creative, understandable manner that engages senior management;
- Strong interpersonal and teamwork skills.
Qualifications - Preferred
- Experience of writing SQL queries to extract/interrogate relational databases;
- Experience in using AWS Cloud machine learning services – AWS Cloud Solution Architect certification would be advantageous;
- Understanding of data warehousing concepts and methodologies;
- Knowledge of deploying statistical models and machine learning algorithms into a production operational environment or AWS Sagemaker using containerization;
- Ability to develop visualisations using Tableau software;
- Experience from a previous role in the insurance industry;
- Econometric and/or housing and mortgage market knowledge.