Nisanth S

karur, Tamilnadu 65 · Good

About

No bio added yet

Skills & Expertise (26)

Python Advanced

8.0/10

Years Exp

Pandas Advanced

8.0/10

Years Exp

Exploratory data analysis Advanced

8.0/10

Years Exp

Data Visualization Advanced

8.0/10

Years Exp

Regression Intermediate

7.5/10

Years Exp

Classification Intermediate

7.5/10

Years Exp

Random Forest Intermediate

7.5/10

Years Exp

NumPy Intermediate

7.5/10

Years Exp

Git Intermediate

7.0/10

Years Exp

Tableau Intermediate

7.0/10

Years Exp

Statistical Analysis Feature Engineering Data Modelling DAX Power Query Dashboard Development Data Wrangling Report Publishing Business Intelligence Reporting Matplotlib Seaborn Predictive Modelling Text Preprocessing MySql Jupyter Notebook Logistic Regression

Work Experience

Data Analyst

TCS

Present - Present

Developed an end-to-end machine learning pipeline to forecast TCS stock prices using historical market data, applying Linear Regression and Random Forest models. Conducted comprehensive EDA to identify key price-influencing features including trading volume and moving averages, achieving significant RMSE reduction. Visualized model performance and stock trends using Matplotlib and Seaborn, enabling clear communication of insights to stakeholders. Demonstrated proficiency in full data science lifecycle: data collection, preprocessing, model training, evaluation, and reporting.

Data Analyst

E-Commerce

Present - Present

Performed end-to-end data analysis using SQL, leveraging JOINs, CTEs, subqueries, aggregations, CASE statements, and window functions to analyse sales, revenue, customers, products, and regional performance. Developed an interactive Power BI Business Intelligence dashboard with KPI reporting, data modelling, data transformation, trend analysis, customer analytics, product performance, slicers, filters, and drill-downs. Identified sales trends, customer purchasing patterns, top-performing products, and regional opportunities, translating findings into actionable business insights and data-driven recommendations.

Data Analyst

Customer Churn Prediction

Present - Present

Performed data cleaning, data validation, exploratory data analysis, and feature engineering to identify churn drivers. Analysed customer attributes including tenure, monthly charges, and contract type to identify factors influencing customer churn. Developed a Random Forest classification model achieving approximately 85% classification accuracy through systematic hyperparameter tuning. Transformed analytical findings into business-ready reports and actionable retention insights. Applied data analysis techniques to support data-driven decision-making and performance evaluation.