QBE is looking to enhance the scientific integrity of their work products in assigned business areas by leveraging data science projects, providing data modelling and analysis support, and optimizing processes through Machine Learning. The goal is to improve decision-making, operational efficiency, fraud identification, recoveries, renewals, and profitable growth.
Requirements
- Experience in producing insights from large datasets using R, Python, Spark.
- Collaborative programming project experience.
- Comfortable working in a Linux environment.
- Knowledge of Computer Science Fundamentals, Probability and Statistics, Data Modelling, Machine Learning Algorithms, Software Engineering.
Responsibilities
- Conduct exploratory data analysis to obtain insights using analytical methods and statistical techniques.
- Solve data issues to provide advice on underwriting policies and to support decision-making and improve operational efficiency.
- Provide subject matter guidance to build and deploy models, and analyse model performance.
- Collaborate with other analytics team members to size analytical opportunities and create delivery plans for positive commercial returns.
- Provide input on analytical models to drive fraud identification, recoveries, renewals, and profitable growth.
- Assist in developing commercial propositions using analytics within insurance core functions.
- Development of own knowledge of new feature sets and explore machine learning algorithms for extracting new features
Other
- Full time
- Employee
- Hybrid (2-3 days in the office)
- Some relevant work experience.
- Tertiary Degree or equivalent combination of education and work experience.
