Areas of responsibility may include but are 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
• Prototyping Natural Language Processing (NLP) and Large Language Model (LLM) business cases
• 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

Personal Attributes and Skills

• Identifying and analysing trends
• Adapting and Responding to Change
• Results orientated and commercial thinking
• Working with People
• Deciding and initiating action
• Applying Expertise and Technology
• Proactivity and accountability
• Advanced Proficiency in MS Word, MS Excel and MS Outlook
• Analytical Skills
• Statistical Skills
• Creating innovating solutions to complex problems
• Writing and Reporting

Education and Experience (Junior Data Scientist role)

Essential:

• Matric with Mathematics
• Honours Degree in either Data Science, Actuarial Science, Statistics, Operations Research, Computer Science or Applied Mathematics
• Demonstrable knowledge and experience in statistical modelling, data mining, machine learning or optimisation
• Ability to formulate a clear problem statement, develop a plan for tackling it, and clearly communicate findings verbally, visually, and in writing.

Advantageous:

• Master’s Degree in either Data Science, Actuarial Science, Statistics, Operations Research, Computer Science or Applied Mathematics
• 1-2 years of working experience as a Data Scientist in the Life Insurance / Financial Services Industry
• Experience in a big data environment such as Databricks, Kubernetes or similar

Knowledge:

• Intermediate to advanced SQL knowledge
• Proficient in at least one of R, Python, Spark interpreters or similar

Education and Experience (Actuarial Analyst role)

Essential:

• Matric with Mathematics
• Honours Degree or equivalent in Actuarial Science,
• At least 6 of the Foundation and Intermediate Technical subjects (A111 – A214) of ASSA, or equivalent, which should include A211 (CT1) and A213 (CT5).
• Ability to formulate a clear problem statement, develop a plan for tackling it, and clearly communicate findings verbally, visually, and in writing.

Advantageous:

• 1-2 years of working experience as an Actuarial Analyst in the Life Insurance / Financial Services Industry
• Demonstrable knowledge in statistical modelling, data mining, machine learning or optimisation
• Good progress towards qualifying as an actuary with a recognised actuarial professional body, e.g. ASSA or IFoA
• Experience in a big data environment such as Databricks, Kubernetes or similar

Knowledge:

• Intermediate to advanced SQL knowledge
• Proficient in at least one of R, Python, Spark interpreters or similar