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Data Analyst with less than a year in Computational Science & Applications, proficient in Python, SQ
Final-year MSc. Computational Science & Applications student at the prestigious Banaras Hindu University, with a proven track record of converting complex data into actionable business decisions. Completed an internship at IIT BHU, gaining hands-on experience in advanced Natural Language Processing and image-based deep learning. Uncovered $2.71M in hidden inventory risk through end-to-end data analysis, demonstrating real-world impact beyond academics. Proficient in Python, SQL, Power BI, and Machine Learning, with a keen eye for identifying patterns, optimising performance, and solving complex problems. A quick learner with strong communication and leadership skills, eager to contribute technical expertise and innovative thinking to any data-driven team.
Banaras Hindu University
MSc. · Computational Science and Applications
August 1, 2024 – June 30, 2026
Magadh University
Bachelor of Computer Applications
August 1, 2020 – June 30, 2023
Bihar School Examination Board, Patna
Intermediate
June 1, 2019 – May 31, 2019
Central Board of Secondary Education, Delhi
Matriculation
June 1, 2017 – May 31, 2017
Atulya Pvt. Ltd.
Data Analyst Intern
May 1, 2026 – June 1, 2026
India
IIT BHU
Research Intern
June 1, 2025 – September 1, 2025
India
Code Smell Detection Using Machine Learning
June 1, 2026 – June 1, 2026
• Built a machine learning model to automatically detect code smells — including Long Method, God Class, Duplicate Code, and Feature Envy — from source code metrics. • Carried out data preprocessing, feature selection, and normalisation on a software metrics dataset. • Assessed model performance using accuracy, precision, recall, and F1-score, and visualised results through a confusion matrix.
Vendor Performance Analysis
May 1, 2026 – June 1, 2026
• Designed and optimised a SQL-based ETL pipeline using Common Table Expressions (CTEs) and advanced filtering techniques. • Conducted exploratory data analysis and hypothesis testing to assess vendor profitability and inventory turnover. • Identified key operational risks, including high dependency on top vendors, and discovered $2.71M worth of unsold inventory. • Developed interactive Power BI dashboards to effectively visualise and communicate key vendor performance metrics.
The Joy of Computing using Python
NPTEL
June 1, 2026 – Present
Education Leadership
NPTEL
June 1, 2026 – Present
Cloud Computing
NPTEL
June 1, 2026 – Present
Advanced Diploma in Information Technology and System Management
Unknown
June 1, 2026 – Present
Cultural Fit Analysis
The candidate's projects demonstrate a blend of academic rigor (Code Smell Detection) and practical business application (Vendor Performance Analysis). The diverse skill set (SQL, Python, Power BI, Machine Learning) and exposure to different types of data problems (business performance, software metrics, image/text data) suggest adaptability and a broad interest in data science, which could be a good cultural fit for a dynamic data team. The ongoing Master's degree indicates a commitment to continuous learning.
Soft Skills & Operational Fit
The candidate highlights teamwork, time management, leadership, communication, adaptability, and work ethic as soft skills. The project descriptions indicate an ability to work on data-driven problems and communicate findings effectively through dashboards. The academic background in Computational Science and Applications suggests a structured approach to problem-solving.