Data Scientist (Intermediate)

 

Discovery Health

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, self-driven 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 Data Science Lab (DS Lab) is expanding, and we’re looking for talented individuals to join our growing team. Our global team collaborates with partners such as Discovery Health Digital, Quantium, Risk Intelligence, and renowned institutions like the London School of Economics (LSE). Working across diverse areas—including digital, clinical, wellness, and behavioral themes—we harness terabytes of structured and unstructured data using a modern big data architecture. The DS Lab also embraces a forward-thinking approach, identifying new data sources and opportunities and leveraging the Vit.AI platform, we create scalable, fit-for-purpose solutions that serve the business well into the future.  

 

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

 

 

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.