Abhishek Kumar Gupta

0+ yrs exp 77 · Very Good

About

Computer Science graduate (2026) with practical experience in Data Engineering, Machine Learning, and Data Analytics. Proficient in Python, SQL, ETL, data pipelines, Azure Data Factory, Azure Databricks, Power BI, Pandas, and NumPy. Experienced in developing machine learning and data-driven solutions, with hands-on project experience in multilingual phishing detection and customer lifecycle analytics. Strong foundation in data processing, analytics, and transforming complex datasets into actionable insights.

Skills & Expertise (36)

NLP Advanced

9.0/10

Years Exp

Supervised Learning Advanced

8.5/10

Years Exp

Python Advanced

8.5/10

Years Exp

Data Processing Advanced

8.0/10

Years Exp

Pandas Advanced

8.0/10

Years Exp

NumPy Advanced

8.0/10

Years Exp

SQL Advanced

7.5/10

Years Exp

Power BI Advanced

7.5/10

Years Exp

ETL Advanced

7.0/10

Years Exp

Git Advanced

7.0/10

Years Exp

Data Pipelines Intermediate

6.5/10

Years Exp

Java Intermediate

5.5/10

Years Exp

Hadoop SDLC MySql relational databases VS Code Jupyter Notebook OOP DBMS Computer Networks REST APIs Azure Databricks Azure Data Factory ROC-AUC Confusion Matrix F1-Score Recall Precision Accuracy Random Forest Logistic Regression TF-IDF Text Preprocessing Feature Engineering Classification

Work Experience

Final Year Project

ITER, Siksha ’O’ Anusandhan University

Dec 2025 - Present

Developed a machine learning-based system to detect spam, phishing, and fraudulent messages in English, Hindi, and Hinglish. Applied NLP preprocessing and TF-IDF features with word and character n-grams for text classification. Achieved 98.8% accuracy and 99.37% F1-score using Linear SVM.

E-Commerce & Delivery Analytics Platform

ShopPulse

Present - Present

Developed an interactive Power BI analytics platform to analyze e-commerce sales, customers, orders, products, and delivery performance. Performed data cleaning, transformation, and ETL using Power Query, SQL, and Python/Pandas. Built interactive dashboards, KPIs, slicers, and DAX measures to track revenue, sales trends, customer behavior, and delivery metrics. Created a structured data model with relationships to enable dynamic and cross-table business analysis.