Data Scientist at Discovery Limited

Key Purpose

The Data Science Lab is a highly specialised and growing team that tackles challenges in the health, life, and short-term insurance businesses, as well projects that cut across the whole of the Discovery Group related to improving customer service, optimising efficiency, and driving new business.

Key Outputs

We have a vacancy for a data scientist to work on cutting edge NLP projects. The projects include bespoke sentiment and topic models, as well as the use and fine-tuning of a large language model which will integrate into our CRM system to enrich the ways operations teams engage with complex information, thus enhancing servicing initiatives.

Responsibilities include:

• Mining and visualising large structured and unstructured datasets throughout the businesses to find new insights to inform product design, risk management, sales initiatives, operational efficiency, and customer interaction strategies.
• Following model implementations from prototyping through to business adoption.
• Monitoring model performance and using feedback for improvement.
• Improving business processes and data collection where opportunities arise.

Competencies

• A creative and enthusiastic attitude to unearthing valuable insights and generating value for Discovery clients
• Ability to balance multiple priorities and to step back and see how analytics work fits into the wider business context
• Aligned to Discovery values and core purpose

Experience and Qualifications

• Honours or Master’s degree in Data Science, Actuarial Science, Statistics, Operations Research, Industrial engineering, Applied Mathematics,Computer Science, or similar quantitative field.
• Solid understanding of statistics and experience in at least one statistical modelling language
• Good experience with writing queries in SQL
• Some exposure to big data tools and programming languages is preferred, e.g. Spark, Scala
• Ability to formulate a clear problem statement, develop a plan for tackling it, and clearly communicate findings verbally, visually, and in writing
• Ability to source and combine data from both structured and unstructured sources
• Experience in using and/or developing NLP packages and models
• Experience using machine learning frameworks (e.g. Tensorflow) for training deep learning models is advantageous