Key Purpose<\/p>\n
\tIn this role you will be involved in creating opportunities that delight our customers by leveraging Discovery\u2019s vast clinical, demographic and operational data. Using this data with predictive modelling and machine learning techniques you will have a direct impact on strategic initiatives to support Discovery\u2019s world-class operations. The successful applicant will be working within a highly specialized and growing team investigating ways to optimize and improve client services for Discovery\u2019s client schemes.<\/p>\n
Areas of responsibility may include but not limited to<\/p>\n
\tConnecting with a multitude of stakeholders to understand the data in a healthcare and operational context
\n\tMining large structured and unstructured datasets to find new insights to inform operational efficiency and \u2018member- delight\u2019 interaction strategies
\n\tResearch and application of the most up to date machine learning algorithms and AI techniques
\n\tCollaborate with product owners, project managers, and executive stakeholders to identify and prioritize business problems that can be solved with LLMs.
\n\tConduct desktop research into the state-of-the-art in LLMs and Generative AI and apply findings to real-world applications (either requested by business or suggested by yourself).
\n\tPresent data and model findings in a way that provides actionable insights to business users
\n\tMonitoring model performance
\n\tImprove processes and databases where opportunities arise<\/p>\n
Personal Attributes and Skills<\/p>\n
\tExpert in data science programming languages such as R, Python, Scala
\n\tExpert in data manipulation skills including SQL to extract, transform and load data
\n\tExperience in interactive data exploration and data-driven story telling
\n\tUnderstanding and application of Big Data and distributed computing principles
\n\tHands on experience with Big Data systems will be preferred
\n\tStrong analytical and statistical knowledge with an understanding of the latest machine learning algorithms for both structured and unstructured data
\n\tAbility to adapt to emerging technologies and tools
\n\tProficiency in version control systems such as Git for collaborative coding and maintaining code integrity
\n\tAbility to formulate problem statements and develop a plan for tackling the problem
\n\tStrong ability to communicate findings and recommendations from data (visual, verbal and written)
\n\tIntegration and implementation experience
\n\tA passion for data exploration and analytics
\n\tSelf-starter
\n\tWillingness to learn and grow exponentially
\n\tA restless curiosity towards data and uncovering unknown correlations
\n\tAbility to work cohesively in a team environment and balance multiple priorities
\n\tA team player who can work alone when required and without supervision
\n\tHigh level of attention to detail, resilience, enthusiasm, energy and drive<\/p>\n
Education and Experience<\/p>\n
\tHonours or Master\u2019s degree in Computer Science with solid experience in statistical modelling, data mining and machine learning, OR
\n\tHonours or Master\u2019s 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
\n\tOther analytical qualifications will also be considered if accompanied by the relevant experience
\n\tA minimum of 2 years\u2019 work experience in a data science position<\/p>\n
go to method of application \u00bb<\/p>\n
Apply via company website ( ) or<\/p>\n
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