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Data Science with less than a year in Python, Machine Learning, NLP, SQL, and Data Visualization.
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Assessing your cultural and operational fit
B.Tech ECE graduate with hands-on experience in Python, Machine Learning, NLP, SQL, and Data Visualization. Proficient in writing SQL queries for data extraction and analysis, building end-to-end ML pipelines, and creating interactive Tableau and Power BI dashboards to communicate data insights. Certified in Data Science & AI. Seeking a fresher role in Data Science, ML, or Analytics.
Boston Institute of Analytics
Certification · Data Science & Artificial Intelligence
August 1, 2025 – June 30, 2026
Sri Manakula Vinayagar Engineering College
B.Tech · Electronics & Communication Engineering
August 1, 2021 – June 30, 2025
ST. Patrick Higher Secondary School
HSC
June 1, 2021 – May 31, 2021
Maruthi Higher Secondary School, Puducherry
SSLC
June 1, 2019 – May 31, 2019
E-Commerce Customer Segmentation & Prediction
January 1, 2025 – December 31, 2025
Queried and extracted customer transaction data using SQL wrote JOINS, GROUP BY, and aggregate functions to build RFM (Recency, Frequency, Monetary) features before loading into Python for analysis. Applied multiple clustering algorithms - K-Means, DBSCAN, and Hierarchical Clustering and used the Elbow Method and Silhouette Score to determine optimal customer segments. Built classification models (Logistic Regression, Random Forest, XGBoost) to predict customer segment labels, achieving strong accuracy with cross-validation. Designed an interactive Tableau dashboard to visualize customer segments with filters by region, spend range, and segment type - enabling business teams to explore insights without coding. Visualized feature distributions and segment patterns using Seaborn and Matplotlib to derive actionable business insights.
Multi-Label Classification of Customer Support Tickets
January 1, 2025 – December 31, 2025
Fine-tuned a pre-trained BERT model for multi-label text classification to automatically categorize customer support tickets into 5 categories, achieving 82% accuracy. Handled class imbalance using oversampling and class weighting, improving model stability and prediction accuracy. Implemented advanced text preprocessing - lowercasing, punctuation removal, tokenization - reducing noise by 35% and enhancing model generalization. Optimized hyperparameters and applied data augmentation, increasing classification performance by 25% over baselines. Developed a FastAPI endpoint for real-time ticket classification, enabling automated ticket routing and faster response times.
Sales Performance Dashboard - Tableau & SQL
January 1, 2025 – December 31, 2025
Analyzed the Superstore retail dataset (10,000+ sales records) using SQL to extract, clean, and summarize sales, profit, and customer data. Developed an interactive Tableau dashboard with visualizations for regional sales, profit analysis, monthly trends, and category performance, including filters for Region, Year, and Category. Identified key insights and published the dashboard on Tableau Public.
View ProjectCLA: Programming Essentials in C
Unknown
June 1, 2026 – Present
Kaggle - Data Visualization
Kaggle
June 1, 2026 – Present
IT Specialist – Python
Unknown
June 1, 2026 – Present
Kaggle - Pandas
Kaggle
June 1, 2026 – Present
Kaggle - SQL
Kaggle
June 1, 2026 – Present
MathWorks - Computer Vision Onramp
MathWorks
June 1, 2026 – Present
Kaggle - Intro to Machine Learning
Kaggle
June 1, 2026 – Present
Cultural Fit Analysis
The candidate's academic projects show a strong alignment with the Data Science target role, covering various aspects from data manipulation to model deployment and visualization. The breadth of technologies used (Python, SQL, Tableau, Scikit-learn, BERT, FastAPI) indicates a willingness to explore and adopt diverse tools. The academic nature of all projects, however, means there's no direct evidence of collaboration within a professional team setting or experience with real-world business constraints beyond academic scenarios.
Soft Skills & Operational Fit
The candidate demonstrates a project-oriented approach, indicating a proactive attitude towards learning and applying technical skills. The detailed project descriptions suggest an ability to articulate technical processes and outcomes. However, without direct work experience, it's difficult to assess operational fit, teamwork, or stress handling capabilities.