Masters or PhD degree in either Data Science, Actuarial Science, Statistics, Operations Research,
Computer Science or Applied Mathematics
Ability to formulate a clear problem statement, develop a plan for tackling it, and clearly communicate findings verbally, visually, and in writing
Demonstrable working experience in an analytics position, where the focus was on building and implementing machine learning models to solve business problems
Experience accessing and analysing data using language/tools/databases such as Python, R, SQL,
etc. * Experience using Gradient Boosting Machines, Random Forests, Neural Networks or similar algorithms.
Good knowledge of Microsoft Office tools
Responsibilities:
Identify and build appropriate models to predict risk, sales and savings
Present data insights and model findings in a way that provides actionable insights for business stakeholders and senior executives
Mining and visualising large structured and unstructured datasets throughout the businesses to inform product design, risk management, customer interaction strategies, etc.
Following model implementations through to business adoption
Monitoring model performance and using feedback for improvement
Improving processes and data collections where opportunities arise
Running scientific experiments to evaluate different models in a reproducible way
Produce analytical work that is customer, business and staff focused