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Imagine a world where people live healthier, more enhanced and protected lives… A world in which each organisation is a powerful influencer and responsible corporate citizen, committed to being a force for social good. As a leading innovator in healthcare, wellness, insurance, investments, financial and life planning, Discovery works ceaselessly to...
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Key Purpose
The Individual Life Analytics team is responsible for strategic and impactful projects for the business. The focus of this role will be to support development and implementation of data science projects in the Advanced Analytics (Data Science) function of the team. The role involves exposure to a wide range of business areas such as underwriting, claims, legal and other operations, as well as the wider Discovery Group.
Areas of responsibility may include but not limited to
Mining large structured and unstructured datasets for data exploration to find new insights
Perform data investigations to inform operational efficiency and interaction strategies
Transform data into meaningful model inputs and data pipelines
Develop and refine predictive models such as fraud, underwriting and customer behavioural models
Support model implementation and monitoring of model performance
Further develop existing models and research new techniques to fully utilise the rich Discovery data universe
Participate in the wider Discovery Data Science community.
Education and Experience
Essential:
Matric with Mathematics
Honours Degree in either Actuarial Science, Data Science, Mathematical Statistics, Operations Research or Applied Mathematics with some experience in data science, computer science or regularly working with big structured / unstructured sets of data OR
Honours Degree in Computer Science or Software Engineering with solid experience in statistical modelling, data mining, machine learning or optimisation
At least 2 years of work related experience
Advantageous:
3-5 years of working experience as an Actuary in the Life Insurance industry
Master's Degree in Computer Science / Software Engineering / Data Science / Statistics / Operations Research / Applied Mathematics
3-5 years of working experience as a Data Scientist in the Life Insurance / Financial Services Industry
3-5 years of working experience in Problem Solving and Data Analysis
Qualified / near-qualified actuary with recognised actuarial professional body, e.g. ASSA or IFoA
Experience in a big data environment such as Cloudera or similar
Knowledge:
Intermediate to advanced SQL knowledge
Proficient in at least one of R, Python, Spark interpreters or similar
Technical Skills and Knowledge
Essential:
Intermediate to advanced SQL knowledge
Proficient in at least one of R, Python, Spark interpreters or similar
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