Key Purpose<\/p>\n
The Data Science Lab is a highly specialised and expanding team that is dedicated to creating long-lasting, impactful solutions to meet essential business needs. Our primary objectives include:<\/p>\n
\tDeveloping and maintaining robust capabilities that will serve the business for years to come, with the goal of helping our members lead healthier lives.
\n\tRisk management through behavioural science and intervention (next best action) design.
\n\tCombining traditional data (e.g. wearable devices, web & app logs, health & life insurance claims) with novel data sources in new ways.
\n\tEmploying Large Language Models to elevate our servicing and coaching capabilities.
\n\tAssisting with experimental design for product, rewards, marketing, communications, engagement, etc.
\n\tFostering a culture of experimentation through a test-learn-adapt approach, ensuring continual improvement and innovation.
\n\tAdvising global partner markets on how to customise and deploy locally built models.
\n\tIndividuals with two to five years\u2019 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. The innovative work environment means there are opportunities to shape new projects with a focus on helping insurance customers to lead healthier lives.<\/p>\n
Areas of responsibility may include but not limited to<\/p>\n
Data analysis and modelling<\/p>\n
\tExtracting and analyzing clinical, lifestyle, and behavioral data to inform product design, risk management, customer interaction strategies for Personalised Health Pathways (PHP).
\n\tDeveloping and maintaining predictive, value and habit models and algorithms to drive personalised recommendations.
\n\tDeveloping data science models and A\/B testing pipelines for deployment.
\n\tApplying statistical techniques, behavioral science principles, and data science models to measure and optimise member engagement.<\/p>\n
Collaboration with Cross-functional Teams<\/p>\n
\tWorking closely with Vitality, clinical, product, and research teams to ensure insights and modelling inputs\/outputs align with product objectives and healthcare outcomes
\n\tCollaborate with systems and engineering teams to integrate data science pipelines into downstream systems.<\/p>\n
Reporting and Insights<\/p>\n
\tPresent insights and results to business stakeholders and senior executives, highlighting the impact of personalised health journeys on user engagement and long-term health improvements.<\/p>\n
Personal Attributes and Skills \u00a0<\/p>\n
\tA creative and enthusiastic attitude to unearthing valuable insights and generating value for Discovery clients
\n\tAbility to balance multiple priorities and to step back and see how analytics work fits into the wider business context
\n\tResults driven, curious and able to work autonomously or within teams
\n\tGood time and task management skills
\n\tAbility to communicate results of analyses in a clear and effective manner
\n\tAligned to Discovery values and core purpose\u00a0<\/p>\n
Education and Experience<\/p>\n
\tHonours, Master\u2019s or PhD degree in either Data Science, Actuarial Science, Statistics, Operations Research, Computer Science or Applied Mathematics.
\n\tAbility to formulate a clear problem statement, develop a plan for tackling it, and clearly communicate findings verbally, visually, and in writing.
\n\tDemonstrable working experience in an analytics position, where the focus was on building and implementing machine learning models to solve business problems.
\n\tExperience accessing and analysing data using language\/tools\/databases such as Python, R, SQL, etc.
\n\tExperience using Gradient Boosting Machines, Random Forests, Neural Networks or similar algorithms.
\n\tGood knowledge of Microsoft Office tools.<\/p>\n
Advantageous:<\/p>\n
\tSome experience in working with big disparate sets of data and exposure to big data tools.
\n\tThe ideal candidate will possess a deep interest in the wellness and healthcare industries, particularly in leveraging behavioural science to promote healthier lifestyles, disease management and prevention. Additionally, they should demonstrate a strong understanding of strategic risk management principles and their application across the healthcare value chain.<\/p>\n
go to method of application \u00bb<\/p>\n
Apply via company website ( ) or<\/p>\n
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