About (Data Science Unit

The Risk Intelligence team is responsible for the measurement and reporting of clinical experience for each of our client schemes, providing actuarial analytic support for managed care interventions, healthcare quality public reporting initiatives, provider contracting, and clinical profile reports of clinician utilisation patterns and adherence to evidence based clinical process measures.

Key Purpose

In this role you will be involved in creating opportunities that delight our customers by leveraging Discovery’s vast clinical, demographic, and operational data. The successful applicant will be working within a highly specialized and growing team investigating ways to optimize and improve client services for Discovery’s client schemes. The successful candidate must be motivated, productive and work well within a team.

Areas of responsibility may include but not limited to

• Connecting with a multitude of stakeholders to understand the data in a healthcare context
• Mining large structured and unstructured datasets to find new insights to inform healthcare efficiency and interaction strategies
• Research and application of the most up to date machine learning algorithms and AI techniques
• Present data and model findings in a way that provides actionable insights
• Implementing results for use in both the internal and external environments
• Monitoring model performance
• Improve processes and databases where opportunities arise

Personal Attributes and Skills

• Expert in data science programming languages such as R, Python, Scala
• Expert in data manipulation skills including SQL to extract, transform and load data
• Experience in interactive data exploration and data-driven story telling
• Understanding and application of Big Data and distributed computing principles (Hadoop and MapReduce)
• Hands on experience with Big Data systems will be preferred
• Strong analytical and statistical knowledge with an understanding of the latest machine learning algorithms for both structured and unstructured data
• Ability to formulate problem statements and develop a plan for tackling the problem
• Strong ability to communicate findings and recommendations from data (visual, verbal and written)
• Production environment machine learning and AI
• A passion for data exploration and complex healthcare environment
• Self-starter
• Willingness to learn and grow exponentially
• A restless curiosity towards data and uncovering unknown correlations
• Ability to work cohesively in a team environment and balance multiple priorities
• A team player who can work alone when required and without supervision
• High level of attention to detail, resilience, enthusiasm, energy and drive
• Positive, can-do attitude
• Ethical and able to maintain confidentiality and manage boundaries
• Aligned to Discovery values and core purpose

Education and Experience

• Honours or Master’s degree in either Data Science, Statistics, or Applied Mathematics with some experience in software engineering, computer science or working with big disparate sets of data, OR
• Honours or Master’s degree in Computer Science or Software Engineering with solid experience in statistical modelling, data mining and machine learning
• Other analytical qualifications will also be considered if accompanied by the relevant experience