To drive the data collection, pre-processing and operational analytics within a sub set of data of the Group under the leadership of the Data and analytics officer. To build business analytical models to address business problems and to provide business insight to enable sustainable business growth support and profitability. To analyse large amounts of business and customer data to find patterns to improve the Society’s service offerings and customer experience (CX).

Data management

  • Identify valuable analytical data sources and automate the collection and storage processes to ensure quick access to analytical data when required.
  • Undertake pre-processing of structured and unstructured data to enable accurate analytics.
  • In collaboration with ICT and under supervision of the Data and Analytics officer, design and implement data warehouses and storage for easy retrieval by business of key metrics.
  • Assist with the implementation of the Groups data management programme including data technologies, processes, and policies across the business.
  • Expanding and enriching the Society’s data with third party sources of information when needed.
  • Enhancing direct and indirect data collection procedures to include information that is relevant for building analytic systems.
  • Processing-, cleansing-, and verifying data collected and retained to improve the integrity of data used for analysis.


  • Perform operational data analytics and forecasting using information within the Group to optimise business performance within a sub-set of data.
  • Selecting features, building and optimizing classifiers using machine learning techniques
  • Analyse operational and customer data to uncover and identify trends embedded in the data using state-of-the-art methods.
  • Doing ad-hoc operational analysis, review the data and present findings (results) in a clear manner to the Data and Analytics Officer.
  • Creating automated data anomaly detection systems and constant tracking of its performance.
  • Analyse large amounts of insurance, operational and customer data to discover trends and patterns which could be used to improve operational performance.
  • Build predictive models and machine learning algorithms to solve identified business challenges and requirements e.g. Predictive lapse models.
  • Present information to key business stakeholders for business decision making and performance measurement using data visualisation techniques.
  • Propose solutions to business challenges.
  • Collaborate with relevant business stakeholders where applicable, CX teams and product development teams to optimise business processes, product value propositions and customer experience.


  • Bachelor degree in Data Science, Management Information Systems, Statistics, Analytics or related field.
  • Knowledge of R, SQL and Python will be advantageous.


  • 3- 5 years’ experience with a proven track record in data science or services industry.
  • Experience in design, development, verifications and validation of applied, descriptive, prescriptive and predictive analytics.
  • Experience in data mining
  • Knowledge of sales and marketing strategies and tactics.


  • Analytical mind and business acumen
  • Strong maths and statistics skills
  • Problem solving aptitude
  • Relationship building and networking
  • Problem solving and innovation
  • Well-developed communication and presentation skills (written and verbal)
  • Stress tolerance and excellent communication skills

Desired Skills:

  • Problem solving aptitude
  • Strong mathematical and statistic skills
  • Excellent communication skills
  • Relationship building and networking
  • Analytical mind and business acumen
  • R
  • SQL
  • Python
  • Sales and marketing strategies and tactics

Desired Work Experience:

  • 2 to 5 years Data Analysis / Data Warehousing

Desired Qualification Level:

  • Degree

Employer & Job Benefits:

  • Pension
  • Maternity leave
  • Medical Aid

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