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, 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 DS Lab is growing and positions are available. The lab applies predictive analytics, machine learning, big data, and operations research skills to run and support key projects for the Group and for the individual Discovery business units. We work across clinical, wellness, financial, sales, operational, people, and behavioral 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 specialized and expanding team that tackles challenges in the health, life, and short-term insurance businesses, as well as 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 behavioral science and intervention (next best action) design.
- Combining traditional data (e.g., wearable devices, 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 customize 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 are 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 visualizing 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 analyzing 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.
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