Key accountabilities

Accountability: Data Analysis & Modeling – 45%

• Collect, clean, and preprocess structured and unstructured data from various sources.


• Perform exploratory data analysis (EDA) to uncover trends, correlations, and anomalies.


• Develop, test, and validate predictive models and machine learning algorithms to solve key problems or exploit opportunities including but not limited to:

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  • Fraud detection
  
  
  • Marketing personalisation
  
  
  • Credit decisioning
  
  
  • Customer churn
  
  
  • Product recommendations
  
  
  • Customer experience
  
  
  • Customer interaction
  
  
  • Optimize model performance and ensure scalability for deployment in production environments.
  
  
  
  

Accountability: Business Insight & Communication – 35%

• Translate complex analytical results into clear, actionable business insights.


• Create dashboards, visualizations, and reports to communicate findings to stakeholders.


• Present data-driven recommendations to both technical and non-technical audiences.


• Support strategic decision-making by aligning insights with business objectives.

Accountability: Collaboration & Data Governance – 20%

• Partner with cross-functional teams (e.g., IT, Product Team, Marketing & Customer Experience) to integrate data science solutions into business processes.


• Ensure data quality, integrity, and consistency across systems and workflows.


• Adhere to ethical standards and data privacy regulations in all data handling activities.


• Contribute to the development and maintenance of data governance frameworks and best practices.

Role/person specification

Preferred Education

• Bachelor’s or master’s degree in data science, Computer Science, Statistics, Mathematics, or a related field.


• Relevant professional certifications in data science, analytics, machine learning, artificial intelligence, and cloud platforms are considered added advantages

Preferred Experience

• At least 5 years’ experience in working with big data sets


• Financial domain knowledge is an added advantage

Knowledge And Skills

• Technical Proficiency – Strong foundation in statistics, machine learning, programming (Python, R, SQL), data visualization, and cloud platforms.


• Analytical & Problem-Solving Skills – Ability to work with complex datasets, perform advanced analysis, and extract actionable insights with attention to detail.


• Communication & Collaboration – Skilled in conveying technical findings to diverse audiences and working effectively within cross-functional teams.

Education

• Bachelor`s Degrees and Advanced Diplomas: Physical, Mathematical, Computer and Life Sciences (Required)

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