Data Scientist – Machine Learning & Analytics

About the role

We are looking for a Data Scientist to apply data mining, statistical analysis and machine-learning techniques to large structured and unstructured data sets. The role involves turning complex data into actionable insights that support sound business decisions, particularly within the banking sector.

Key responsibilities

• Develop and deploy machine-learning and statistical models to solve business problems such as credit risk, churn and propensity.
• Perform data preprocessing, cleansing and feature engineering to improve model performance.
• Analyse large datasets to identify patterns, trends and insights for decision-making.
• Design, build and maintain data pipelines and ETL processes that support analytics workflows.
• Translate business requirements into data-science solutions in collaboration with stakeholders.
• Present findings through visualisations and reports using Power BI or Tableau.
• Support model deployment, integration into production systems and ongoing performance monitoring.

Required profile

• 3–4 years of experience in data & analytics or data monetisation.
• Hands-on experience with both structured and unstructured data.
• Strong knowledge of data architecture, ETL processes and data flows.
• Understanding of banking data, systems and products.
• Exposure to software engineering, BI and project delivery.

Required skills

• Proficiency in SAS, R or Python.
• Experience with visualisation tools such as Power BI and Tableau.
• Machine-learning modelling and predictive analytics.
• Data mining, statistical analysis and feature engineering.
• Building and maintaining data pipelines and ETL workflows.