• 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.

• 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)