Junior Data Scientist | Actuarial Analyst - Discovery Life
Discovery Life
Junior Data Scientist | Actuarial Analyst
Advanced Analytics
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 Discovery Life
Discovery Life is an ever growing fast-paced and dynamic environment that provides innovative risk assurance to individual clients. This environment thrives on customer engagement and customer experience as well as mutually beneficial relationships with our brokers and other stakeholders. It is important for our employees to provide a world class service to our internal and external clients, thereby ensuring long and sustainable relationships.
Advanced Analytics function and opportunities available
The Individual Life Analytics team is responsible for strategic and impactful projects for the business. The focus of the team is to support development and implementation of data science projects in the Advanced Analytics (Data Science) function of the team. The available roles involve 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 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
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.