Sujata Nikhade

Data Science graduate

Nagpur, Maharashtra 0+ yrs exp 81 · Excellent

About

Data Science graduate (B.Tech CSE, CGPA 8.86) with a hands-on foundation in Python, SQL, and Machine Learning across data preprocessing, EDA, feature engineering, and model building/evaluation. Experienced applying supervised learning (Random Forest, Logistic Regression) to real-world prediction problems, with hyperparameter tuning for model optimization. Comfortable working end-to-end from raw data to business-ready insight, using visualization tools (Matplotlib, Seaborn, Power BI) to communicate findings.

Skills & Expertise (23)

SQL Intermediate

5.5/10

0.5

Years Exp

Supervised Learning Intermediate

5.5/10

0.5

Years Exp

Model Evaluation Intermediate

5.5/10

0.5

Years Exp

Data Visualization Intermediate

5.5/10

0.5

Years Exp

Feature Engineering Intermediate

5.5/10

0.5

Years Exp

Data Preprocessing Intermediate

5.5/10

0.5

Years Exp

Exploratory data analysis Intermediate

5.5/10

0.5

Years Exp

scikit-learn Intermediate

5.5/10

0.5

Years Exp

Pandas Intermediate

5.5/10

0.5

Years Exp

Python Intermediate

5.5/10

0.5

Years Exp

Matplotlib Intermediate

5.5/10

0.5

Years Exp

Seaborn Intermediate

5.5/10

0.5

Years Exp

NumPy Intermediate

5.0/10

0.5

Years Exp

Statistical Analysis Intermediate

5.0/10

0.5

Years Exp

Excel Intermediate

5.0/10

0.5

Years Exp

MySql Intermediate

5.0/10

0.5

Years Exp

Git Intermediate

5.0/10

0.5

Years Exp

Jupyter Notebook Intermediate

5.0/10

0.5

Years Exp

Feature Selection Intermediate

5.0/10

0.5

Years Exp

Hyperparameter Tuning Intermediate

5.0/10

0.5

Years Exp

Power BI Intermediate

4.5/10

0.5

Years Exp

Data Validation Intermediate

4.5/10

0.5

Years Exp

Algorithm Design Intermediate

4.0/10

0.5

Years Exp

Work Experience

Data Analytics Intern

Codons Technology

Feb 2024 - Aug 2024

Built and evaluated a Random Forest classification model for customer analytics, achieving 82% prediction accuracy — applying core supervised ML techniques (train/test evaluation, feature importance) relevant to production ML workflows. Performed end-to-end data preprocessing, exploratory data analysis (EDA), and feature engineering on raw, unstructured business datasets. Designed data visualizations (Matplotlib, Seaborn) to surface patterns and trends, translating model outputs into stakeholder-facing insights. Identified and validated key drivers of customer churn, contributing data-backed recommendations to the business.