Aspiring data scientist with a passion for leveraging big data to drive insights and innovation. A target-driven individual with an immaculate record of academic success, combined with a wealth of experience handling sub…
Aspiring data scientist with a passion for leveraging big data to drive insights and innovation. A target-driven individual with an immaculate record of academic success, combined with a wealth of experience handling substantial data volumes within the corporate setting. Contributed to one of the biggest companies in the UK; EG Group. Seeking opportunities to further excel in the dynamic field of data science.
Analysed sales data for Beehive, Blackburn – a conglomerate of EG brands, including Starbucks, Subway and Greggs.
Utilised SQL to query and filter data for analysis purposes.
Employed Python to import, clean, and conduct analysis on the data.
Generated visualisations such as time series graphs, regression analysis plots, and boxplots to illustrate sales trends.
Conducted statistical tests on variables influencing sales, including day of the week and season.
Developed forecasting models leveraging three years of historic data, including ARIMA and basic machine learning techniques.
Presented findings to senior management and stakeholders.
Currently supporting senior members’ projects – including fraud analysis and exploring the new market of EV charging.
Created and presented a PowerBI coffee dashboard, providing actionable insights for the Central Buying Department.
Utilised company learning hours to develop a personal finance tracker using PowerBI - displaying income/expenses, categories for spending, and budgeting.
Led an independent fuel pricing project, using Microsoft Excel for data handling and analysis.
Acquired proficiency in SQL through rigorous daily practice and self-learning initiatives.
Utilised SSMS extensively and gained exposure to SSIS and SSRS.
Upheld database standards across all areas, ensuring data integrity and availability.
Supported database creation, design, and testing efforts, including planning for scalability, and optimising table structures.
Identified and resolved database security vulnerabilities, implementing access controls to safeguard sensitive data.
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