Vijay Keerthi Sai Magi
Glasgow
Summary
Purpose-driven and logical professional with a master’s degree in Advanced Computer Sciences, bringing strong skills in data analysis, business process optimization, and project management. Adaptable and easygoing individual who is Passionate about using data and technology to make a real difference and enhance user experiences,
Overview
4
4
years of professional experience
1
1
Certification
Work History
Customer Service Consultant
Pastdue Credit Solutions
02.2025 - Current
- Representing Thames Water, supporting customers with billing queries, payment plans, and account-related concerns in a respectful and solution-focused manner.
- Used multiple internal systems to manage accounts efficiently, ensuring accurate updates and tailored support in every interaction
Data Analyst Internship
S R Associates
09.2021 - 08.2022
- Created various Excel documents to assist with pulling metrics data and presenting information to stakeholders for concise explanations of best placement for needed resources.
- Produced monthly reports using advanced Excel spreadsheet functions.
Education
Master of Science - Advanced Computer Science
University of Strathclyde
Glasgow, United Kingdom03-2024
Bachelor of Science - Bachelor in Computer Application
Davanagere University
Davanagere06-2021
Skills
Programming & Data Technologies: Python, SQL, MongoDB, Java, C, Hadoop, MapReduce
Machine Learning & Statistical Analysis: Scikit-learn, TensorFlow, Keras, Matplotlib, SPSS, Predictive Modeling
Data Visualization & Reporting: PowerBI, Tableau, Advanced Excel
Testing: Knowledge of telecom testing types, tools, and lifecycle; understanding of telecom protocols including SIP, VoIP, LTE
Personal Skills: Documentation, Leadership, Analytical Thinking, Creativity, Problem Solving
Certification
• Data Visualisation in Tableau & Power BI: A course by Data Science Guide on Udemy,
•CBAP - Certified Business Analysis Professional: A course by Edcorner Learning on Udemy.
Projects
- Spotify Music Classification and Regression:
Built ML models using scikit-learn and TensorFlow to classify genres and predict song popularity, achieving 0.35 accuracy with KNN and 10.10 RMSE with Random Forest. - Goodreads Ratings Prediction:
Developed a CNN model with pre-trained GloVe embeddings in TensorFlow/Keras to predict book ratings, reaching 50.8% validation accuracy with consistent performance. - Emotion Recognition from Facial Expressions:
Implemented ensemble deep learning models on the FER 2013 dataset, achieving 63.95% accuracy by combining ResNet, VGG16, and CNN architectures.
Timeline
Customer Service Consultant
Pastdue Credit Solutions
02.2025 - Current
Data Analyst Internship
S R Associates
09.2021 - 08.2022
Master of Science - Advanced Computer Science
University of Strathclyde
Bachelor of Science - Bachelor in Computer Application
Davanagere University
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