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• Collect, clean, and validate large datasets from multiple structured and unstructured sources., • Develop and maintain data pipelines using SQL, Python (Pandas, NumPy), and data integration tools., • Perform statistical analysis and exploratory data analysis (EDA) to identify trends, anomalies, and insights., • Support the design and implementation of predictive models and machine learning algorithms using Python (scikit-learn, TensorFlow, PyTorch) or R., • Create and maintain interactive dashboards and visual reports using Power BI, Tableau, or Qlik., • Collaborate with senior analysts to translate data insights into business recommendations., • Apply data governance and information security best practices throughout all analysis., • Use version control tools (Git/GitHub) and follow agile working methodologies where appropriate., • Contribute to documentation, data cataloguing, and reproducibility of analytical work., • Present findings clearly to non-technical stakeholders through visual storytelling and reports.