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Data Analyst with 1+ years in Python, SQL & AI applications.
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Assessing your cultural and operational fit
Data Analyst with 1+ year of experience in Python, SQL, ETL processes, data modeling, and statistical analysis, specializing in data cleaning, data visualization, and data reporting for analytics and GenAI applications. Evaluated 1,000+ AI-generated responses for quality and accuracy, and built machine learning models achieving up to 90% prediction accuracy.
O.P. Jindal University
B.Sc. · Data Science and Analytics
May 1, 2023 – May 1, 2026
LabelBox
Data Annotator & AI Evaluator
February 1, 2025 – Present
India
Entit Consultancy Pvt. Ltd.
Data Analysis Intern
June 1, 2024 – July 1, 2024
Raipur, Chhattisgarh, India
Customer Purchasing Intention Prediction (Machine Learning Project)
January 1, 2025 – December 31, 2025
Built and compared Logistic Regression, Decision Tree, and Random Forest models to predict purchase intent using the Online Shoppers Intention dataset. Performed data preprocessing and data mining: handled missing values, encoded categorical variables, and applied feature scaling. Achieved ~90% accuracy and AUC ~0.92 with Random Forest, evaluated via precision, recall, F1-score, and confusion matrix. Identified key purchase drivers (page value, product-related activity, session duration) through statistical analysis to inform customer targeting strategies.
SQL (Basic)
HackerRank
June 1, 2026 – Present
Data Analytics with Python
NPTEL
June 1, 2026 – Present
Cultural Fit Analysis
The candidate's academic background in Data Science and Analytics, coupled with an internship and a current role involving AI evaluation, indicates a strong interest and foundational alignment with data-centric roles. The project diversity, from predictive modeling to AI quality assessment, suggests adaptability and a willingness to engage with different facets of data. However, the experience level is junior, which might require mentorship in a senior-level team.
Soft Skills & Operational Fit
The candidate demonstrates a structured approach to data tasks, as evidenced by their project work and internship. Their role as a Data Annotator & AI Evaluator suggests attention to detail and adherence to guidelines, which are valuable for data quality and operational consistency. The academic project highlights problem-solving and analytical thinking.