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Data Preparation

  • Assess the effectiveness and accuracy of new Data sources and Data gathering techniques.
  • Extend the company’s Data with third party sources of information when required.
  • Process, cleanse and verify the integrity of Data used for Analysis.
  • Identify valuable data sources and Automate collection processes.
  • Undertake pre-processing of structured and unstructured data.

Analysis and Model Building

  • Mine and Analyze data to drive optimization and improvement of Pricing, Product development, Marketing techniques, and business Strategies.
  • Analyze large amounts of information to discover trends and patterns.
  • Select features, build, and optimize classifiers using advanced Machine learning techniques.
  • Utilize predictive Modeling to influence value drivers such as sales, client retention, expense management, and optimization of client experience.
  • Develop custom data models and algorithms to apply to data sets.
  • Blend models through ensemble modeling.

Stakeholder Engagement

  • Present information using data visualization techniques.
  • Propose solutions and strategies to business challenges.

Implement and Monitor

  • Coordinate with different functional teams to implement models, allowing for different systems integration patterns, and monitor outcomes.
  • Develop processes and tools to monitor and analyse model performance and data accuracy.

Leadership and Team Management

  • Provide leadership and guidance to team members in Advanced Analytics, the Data engineering and Product development teams.
  • Collaborate with data and analytics experts to enhance workflow processes, documentation, technical model builds and model deployment
  • Support and mentor team members to drive value for the Group.



  • Degree in Statistics, Actuarial Science, Mathematics, Computer Science or another quantitative field.
  •  An advanced degree in a quantitative field would be advantageous.


  • A proven track record of successfully implementing Data-driven solutions and delivering measurable business impact.
  • Demonstrated Leadership and Management abilities: Experience in leading and managing teams, providing guidance and mentorship to junior members, and effectively coordinating with cross-functional teams.

Skills/ Knowledge

  • Strategic thinking: A strategic mindset and the ability to align data science initiatives with broader business objectives. Able to identify opportunities for leveraging data and analytics to drive innovation and improve business outcomes.
  • Technical Expertise: A deep understanding and expertise in various Data science techniques, Statistical modeling, Machine learning algorithms, and Data mining.
  • A thorough knowledge of Programming languages such as Python or R and  proficient in querying databases and working with big data tools and frameworks like Hadoop, Spark, or SQL.
  • Communication and Presentation Skills:  Ability to effectively communicate complex data science concepts and insights to both Technical and non-technical stakeholders.
  •  Excellent presentation skills and the ability to translate data-driven insights into actionable recommendations for business stakeholders.
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