About the Role

Reporting to the Data & Analytics Manager, the Senior Data Scientist will be responsible for developing, deploying, and maintaining data analytics, data science, machine learning, and artificial intelligence solutions that support business decisions.

The role covers the full analytics lifecycle, from exploratory analysis and business intelligence reporting through to feature engineering, model building, deployment, and performance monitoring, with a working understanding of how the underlying data pipelines and warehouses are structured. The role will collaborate with colleagues across the Data & Analytics function and with other stakeholders to build data science and analytics solutions into products, services, customer propositions, and digital channels.

Key Responsibilities

• Perform exploratory data analysis to answer business questions, identify trends, and surface issues that need attention.
• Develop, validate, deploy, and maintain statistical, machine learning, and AI models across customer analytics, segmentation, retention, forecasting, risk, fraud, and optimisation use cases.
• Translate business and customer needs into analytical problems and data science solutions.
• Perform data exploration, feature engineering, model selection, validation, and performance monitoring.
• Build and maintain machine learning pipelines, and deploy solutions into business processes, products, and digital channels.
• Own end to end reporting work, from gathering requirements with business teams through to building dashboards, reports, and visualisations that support business decisions.
• Work with data engineering colleagues on data quality, pipeline structure, and warehouse design where it affects analytical or model work.
• Monitor model performance, data quality, and drift, and keep solutions documented, explainable, and aligned with governance requirements.
• Communicate findings and recommendations to technical and non-technical stakeholders.

Who We’re Looking For

Qualifications

• Bachelor’s degree in Computer Science, Statistics, Mathematics, Data Science, or a related quantitative discipline from a recognised institution.
• Minimum of five (5) years of experience in Data Analytics, Business Intelligence, or Data Science.
• Comfortable working across the analytics stack, from data analysis and BI reporting to model building.
• Strong proficiency in R and/or Python, advanced SQL, and applied statistics, including inference, hypothesis testing, regression, and experimental design.
• Strong understanding of machine learning techniques and algorithms, including model selection, validation, and optimisation.
• Experience working with relational databases, data warehouses, and large datasets, including both structured and unstructured data.
• Experience building dashboards and reports using tools such as Power BI, Tableau, or equivalent.
• Experience with cloud platforms such as AWS, Microsoft Azure, or Google Cloud is an added advantage.
• Strong analytical, problem solving, communication, and stakeholder management skills.

• Perform exploratory data analysis to answer business questions, identify trends, and surface issues that need attention.
• Develop, validate, deploy, and maintain statistical, machine learning, and AI models across customer analytics, segmentation, retention, forecasting, risk, fraud, and optimisation use cases.
• Translate business and customer needs into analytical problems and data science solutions.
• Perform data exploration, feature engineering, model selection, validation, and performance monitoring.
• Build and maintain machine learning pipelines, and deploy solutions into business processes, products, and digital channels.
• Own end to end reporting work, from gathering requirements with business teams through to building dashboards, reports, and visualisations that support business decisions.
• Work with data engineering colleagues on data quality, pipeline structure, and warehouse design where it affects analytical or model work.
• Monitor model performance, data quality, and drift, and keep solutions documented, explainable, and aligned with governance requirements.
• Communicate findings and recommendations to technical and non-technical stakeholders.

• Strong proficiency in R and/or Python, advanced SQL, and applied statistics, including inference, hypothesis testing, regression, and experimental design.
• Strong understanding of machine learning techniques and algorithms, including model selection, validation, and optimisation.
• Experience working with relational databases, data warehouses, and large datasets, including both structured and unstructured data.
• Experience building dashboards and reports using tools such as Power BI, Tableau, or equivalent.
• Strong analytical, problem solving, communication, and stakeholder management skills.

• Bachelor’s degree in Computer Science, Statistics, Mathematics, Data Science, or a related quantitative discipline from a recognised institution.
• Minimum of five (5) years of experience in Data Analytics, Business Intelligence, or Data Science.
• Comfortable working across the analytics stack, from data analysis and BI reporting to model building.
• Experience with cloud platforms such as AWS, Microsoft Azure, or Google Cloud is an added advantage.