Job Summary

Responsible for identifying patterns and trends in complex data sets and developing data-driven algorithms and models to solve key business challenges. By leveraging statistical analysis, machine learning, and data engineering techniques, the role enables value extraction from data and supports strategic, data-informed decision-making across the organization.

Job Description

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:
  • 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.