Data Scientist (Intermediate) at Discovery Limited

Key purpose

The Data Science Lab is dedicated to creating long-lasting, impactful solutions to meet essential business needs. Our primary objectives include:

• Developing personalized models and algorithms aimed at fostering healthy habits, achieving positive health outcomes, and enhancing user engagement with Discovery products and services
• Optimizing customer communication through our expansive data assets
• Employing Large Language Models (LLMs) to elevate our servicing and coaching capabilities
• Fostering a culture of experimentation through a test-learn-adapt approach, ensuring continual improvement and innovation.

Key Outputs

Data analysis and modelling

• Extracting and analyzing digital, clinical and behavioral data to inform product design, customer experience strategies for digital solutions.
• Developing data science model and A/B testing pipelines for deployment.
• Applying statistical techniques, behavioral science principles, and data science models to measure and optimize member engagement and user experiences for digital solutions.

Collaboration with Cross-functional Teams

• Working closely with Discovery Health Digital to ensure insights and modelling inputs align with product objectives and app engagement outcomes.
• Collaborate with systems and engineering teams to integrate data science pipelines into the Health Systems and Health digital solutions.

Reporting and Insights

• Present insights and results to business stakeholders and senior executives, highlighting the impact of personalized digital experiences on user engagement and experience.

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 

Experience, qualifications, and mandatory requirements

• Honours, Master’s 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.

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.
• Individuals with two-five years’ experience (not required but advantageous) in the above areas will have the opportunity to work with cutting edge technology and advanced techniques to see their models used in real business applications