Discovery Health
Senior Data Scientist
About Discovery
Discovery's core purpose is to make people healthier and to enhance and protect their lives. We seek out and invest in exceptional individuals who understand and support our core purpose, and whose own values align with those of Discovery. Our fast-paced and dynamic environment enables smart, selfdriven people to be their best. As global thought leaders, Discovery is passionate about innovating in order to not only achieve financial success, but to ignite positive and meaningful change within our society.
About (Data Science Lab)
The Group DS Lab is growing and positions are available. The lab applies predictive analytics, machine learning, big data and operations research skills, to run and to support key projects for the Group and for the individual Discovery business units. We work across clinical, wellness, financial, sales, operational, people and behavioural theme areas, using modern analytics tools on terabytes of structured and unstructured data within a big data architecture. We are also mandated to find opportunities to use new data sets and in areas not typically accustomed to using data science.
Key Purpose
The Data Science Lab is a highly specialised and expanding 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. We are looking for individuals with 2-5 years of experience, for projects related to:
- risk management through behavioural science and intervention (next best action) design
-combining traditional data (eg: wearable device, web & app logs, health & life insurance claims) with novel data sources in new ways
-assisting with experimental design for product, rewards, marketing, communications, engagement etc
-advising partner markets on how to customise and deploy locally built models
They will have the opportunity to work with cutting edge technology and advanced techniques to see their models used in real business applications. The innovative work environment means there are opportunities to shape new projects with a focus on helping insurance customers to lead healthier lives.
Areas of responsibility may include but not limited to
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
Personal Attributes and Skills
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
Results driven, curious and able to work autonomously or within teams
Good time and task management skills
Ability to communicate results of analyses in a clear and effective manner
Aligned to Discovery values and core purpose
Education and Experience
Master's or PhD degree in either Data Science, Actuarial Science, Statistics, Operations Research, Computer Science, Applied Mathematics or Engineering fields.
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.
Advantageous:
Some experience in working with big disparate sets of data and exposure to big data tools
The ideal candidate will possess a deep interest in the healthcare industry, particularly in leveraging behavioral science to promote disease management and prevention. Additionally, they should demonstrate a strong understanding of strategic risk management principles and their application across the healthcare value chain.
EMPLOYMENT EQUITY
The Company's approved Employment Equity Plan and Targets will be considered as part of the recruitment process. As an Equal Opportunities employer, we actively encourage and welcome people with various disabilities to apply.