• Transformed complex datasets containing customer transaction data into actionable insights by developing interdependent functions and tools for weekly RFM reports, resulting in significant improvement on stakeholders’ understanding of customer segmentations.• Spearheaded the development of BI dashboards utilizing Streamlit and Power BI to visualize key insights to senior management, guiding strategic decision-making processes and driving business growth within the 1st quarter.• Extracted and analysed customer reviews data using advanced data scripts, identifying and flagging negative reviews for prompt resolution by the appropriate teams.

In-depth analysis utilizing a range of SQL queries in MySQL database.Utilized Power BI to visualize datasets, yielding valuable insights and conclusions.

• Employed rigorous statistical analysis techniques to extract actionable insights from complex datasets, leading to an impressive 85% enhancement in data interpretation accuracy. This involved meticulously crafting and executing methodologies to ensure the validity and reliability of findings, showcasing robust problem-solving skills and attention to detail.• Collaborated closely with interdisciplinary researchers, synergizing expertise across fields to develop cutting-edge deep learning models. Leveraging Python packages such as NumPy, Pandas, and Scikit-learn, I engineered sophisticated algorithms tailored to specific research objectives. This collaborative effort resulted in a notable 72% increase in predictive accuracy, demonstrating proficiency in advanced analytical tools and methodologies essential for the role.• Conducted in-depth investigations into various hybrid Recurrent Neural Network models to analyse the dynamics of Bitcoin prices. By meticulously analysing historical data and iteratively refining model architectures, I achieved a significant 75% enhancement in predictive performance. This endeavour underscored adept modelling and optimization skills, crucial for generating actionable insights in dynamic and volatile markets.

• Led a comprehensive simulation project highlighting the pivotal role of data science in driving success for British Airways, meticulously examining the interplay between data-driven insights and operational efficiency.• Spearheaded the development of a sophisticated algorithm for scraping and processing customer review data, leveraging Python and web scraping libraries such as BeautifulSoup and Scrapy, ensuring the acquisition of high-quality, actionable data for analysis. • Designed and implemented a robust predictive model utilizing advanced machine learning techniques, particularly random forest classifiers, to discern key factors influencing consumer purchasing behavior in the aviation sector. This involved meticulous feature engineering, model tuning, and validation procedures to ensure the accuracy and reliability of predictions, resulting in 89% accuracy in prediction accuracy.• Collaborated closely with cross-functional teams to interpret model outputs and provide strategic insights to British Airways stakeholders, facilitating data-driven decision-making processes aimed at enhancing customer satisfaction and loyalty. • Presented findings and recommendations to project stakeholders in a clear and concise manner, emphasizing the significance of data-driven approaches in optimizing business outcomes and informing strategic initiatives within the aviation industry.