As a dedicated and enthusiastic learner in the field of technology, I have a particular interest in data analytics. My education in the field of computer science and my work experience in the tech industry have equipped me with the skills necessary for a successful career in AI and Data Analytics.
Key Skills: SQL, Python Programming, Big Data Analysis, Machine Learning Models, Generative Models, Data Visualisation, Tableau, Power BI, Excel and Project Management
Industry Experience:
Data Specialist at Three UK
• Analyse Financial Data to contribute towards the company revenue models.
• Designed an early indication system that provides key predictions on loan data utilising python and Snowflake skills.
• Optimise current processes and find innovative solutions to new and existing problems.
• Develop Python automation scripts for data processing .
• Design and implement Alteryx ETL pipeline workflows
Project Co-ordinator at IBM
• A collaborative project on enhancing education through AR/VR technology under IBM - Loughborough University partnership program for the Institute of Digital Technologies
• Utilized Python for data processing, cleaning, and predictive analysis, resulting in actionable insights.
• Presented data-driven findings and insights to stakeholders, effectively communicating complex concepts using data visualization tools.
• Collaborated with cross-functional teams to identify opportunities for process improvement through data analysis.
• Created a basic outline for the conceptualisation of Metaverse through IBM watson integration.
Digital Specialist Engineer at Infosys
• Employed logical and analytical skills to troubleshoot application and data-related incidents, effectively identifying root causes and implementing solutions to resolve issues promptly.
• Demonstrated expertise in connecting client data sources, to the company’s data warehouse. Leveraged SQL views to perform data transformations, enhancing data accessibility and analytics capabilities.
• Utilized SQL expertise to extract and analyse data, providing valuable insights that informed the decision to deploy eight new servers. This strategic move reduced repetitive issues and laid the groundwork for future scalability.
• Advised stakeholders on the implementation of a server self-healing model and subsequently designed its workflow process. The successful execution of this model resulted in an impressive 76% accuracy rate, a 31% reduction in server downtime, and the complete elimination of manual intervention.
• Conducted various database administrative tasks, including optimizing SQL queries, and performing CRUD activities such as creating schemas and updating views and tables. These efforts improved database performance and ensured data integrity.
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