Data Scientist
Current• Lead the development of prototypes and extracted actionable insights for Nielsen and BAT-UK by identifying data patterns and operational gaps, improving business strategies and efficiency. • Partnered with cross-functional teams to process and analyse EBM sales data, delivering interactive dashboards that provided key insights and supported data-driven decisions. • Streamlined data preparation for large-scale language models by consolidating datasets into unified formats, ensuring high data quality and optimising model performance. • Led the development of an automated data pipelining system for multidimensional sales analysis, focusing on enhancing the efficiency and accuracy of data processing by implementing a class-based code structure in Python.• Conducted semantic refactoring to transform the existing functional code into a more organized and modular format, aligning it with the entities present in the system.• Utilized Python's advanced libraries and modules for data manipulation, such as Pandas and NumPy, to facilitate data handling and analysis.• Implemented automated data extraction, transformation, and loading (ETL) processes using tools like Apache Airflow data flow and improved data integrity.• Designed and implemented scalable and fault-tolerant data pipelines, integrating various data sources and optimizing the processing speed through parallel computing techniques.•