- 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.
Requirements
- 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.
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