Veerakumar Selvaraj

Data Analyst | Orcalo Holdings                                                                                Jul 2022 to Feb 2023

• Spearheaded the data collection effort through web scraping techniques, extracting structured data from UK government council websites and universities' sites.
• Ensured dataset reliability by meticulously gathering essential attributes like council/university names, contact information, locations, and other pertinent details.
• Applied data cleansing techniques in Excel, identifying and eliminating errors, inconsistencies, and duplicates to enhance data accuracy and integrity.
• Employed Excel’s built-in functions for sorting, filtering, and removing duplicates, streamlining the data cleansing process, and leveraged pivot tables to efficiently summarise and analyse the dataset.
• Collaborated with data architects and analysts to create meaningful data visualisations using Excel's charting capabilities and Microsoft Power BI's interactive dashboards.

Contributed to efficient data management by integrating cleansed data into the JIRA board as user stories and structuring data within Airtable for easy exploratory and team collaboration.

• Software Engineering 1: Acquired in-depth knowledge of object-oriented programming concepts in C# and successfully developed a Sudoku game as a console-based application, showcasing strong programming skills.
• Deriving Value: Data Analytics: Gained a profound understanding of the significance of data collection and analytics in driving data-driven business decisions and acquired skills to implement effective data analytics strategies.
• Statistical Data Analysis and Visualisation: Mastered statistics concepts using R (Programming Language) with hands-on experience in RStudio, enabling data analysis and visualisation.
• Big Data and its Infrastructure: Gained comprehensive insights into various big data infrastructures prevalent in the industry and learned how to effectively implement them for business proposals.
• Applied AI and Data Mining: Proficiently learned and implemented advanced machine learning algorithms such as multi-level perceptron, neural networks, random forest classification, K-means clustering, and computational neural network using Python (Programming Language).
• Main Thesis: Developed a custom machine learning model using the YOLOv8 framework, specifically focused on detecting weeds in corn farm fields, demonstrating strong expertise in computer vision and applied AI.