Nisha Singh

Aspiring Data Analyst

RK nagar mharal gaon Kalyan

Profile Score

About

Aspiring data analyst with a BE in Information Technology and hands-on project experience in data analysis and machine learning. Proficient in Python, SQL, Excel, and data visualization tools like Tableau and Matplotlib. Completed practical projects in churn prediction and sales analytics, showcasing strong skills in EDA, feature engineering, and model development. Eager to apply analytical thinking and technical skills to support data-driven decision-making in a dynamic organization.

Skills & Expertise (21)

Python Advanced

7.8/10

Years Exp

scikit-learn Advanced

7.4/10

Years Exp

Model Building Advanced

7.2/10

Years Exp

Feature Engineering Advanced

7.2/10

Years Exp

Problem Solving Advanced

7.0/10

Years Exp

Effective Communication Advanced

7.0/10

Years Exp

MS Excel Advanced

7.0/10

Years Exp

EDA Advanced

7.0/10

Years Exp

Data Cleaning Advanced

7.0/10

Years Exp

Critical thinking Advanced

7.0/10

Years Exp

Pandas Advanced

7.0/10

Years Exp

Statistical Analysis Intermediate

6.8/10

Years Exp

MySql Intermediate

6.8/10

Years Exp

Matplotlib Intermediate

6.8/10

Years Exp

Evaluation Intermediate

6.8/10

Years Exp

Feature Selection Intermediate

6.6/10

Years Exp

Data Modeling Intermediate

6.6/10

Years Exp

Seaborn Intermediate

6.6/10

Years Exp

NumPy Intermediate

6.6/10

Years Exp

SciPy Intermediate

6.4/10

Years Exp

Power BI Intermediate

6.4/10

Years Exp

Work Experience

Data Analyst Intern

Sevenmind Technology LLP

Jan 2021 - Apr 2021

Conducted data analysis using Python and EDA techniques. Applied feature engineering, imbalanced data handling, and model building on real-world datasets. Contributed to model evaluation and selection processes. Developed a machine learning model to predict customer churn using Python and SQL. Conducted EDA, handled imbalanced data, performed feature engineering, and evaluated multiple models. Enabled proactive retention strategies by identifying churn-risk customers. Analyzed retail sales data to identify key trends and optimization strategies. Created actionable dashboards using Excel and Python visualization libraries. Helped business understand performance metrics and improve inventory management.