Vandana Anand

Data Analyst with a strong foundation in Python, Excel, and data-driven problem solving. Completed a 6-month data science training program focused on data cleaning, exploratory data analysis (EDA), statistical techniques, and building clear visual insights. Skilled in working with datasets using tools such as Pandas, NumPy, Excel PivotTables, and charts to identify trends and support decision-making.

Experienced in preparing reports, dashboards, and actionable insights for non-technical stakeholders. Highly motivated to apply analytical skills in a professional environment and contribute to data-driven business improvements.

Academic / Personal Projects at UNIVERSITY OF EAST LONDON (2025-06 – 2025-09)

• Conducted exploratory data analysis (EDA) using Python (Pandas, NumPy) to identify trends and data quality issues.
• Built basic machine learning models (Linear Regression, Logistic Regression, k-Means) using scikit-learn for predictive analysis.
• Cleaned and prepared datasets by handling missing values, outliers, and transformations.
• Created visualizations with Matplotlib/Seaborn to communicate insights from data.
• Performed basic statistical analysis such as correlation testing and hypothesis testing.
• Analyzed geospatial datasets using QGIS/GeoDa to generate thematic maps and spatial statistics.
• Used SQL to extract, filter, and aggregate data from relational databases.
• Documented project workflow and insights using Jupyter Notebook and Markdown.

Data Science Trainee | 6-Month Intensive Program at CADD NEST (2024-03 – 2024-09)

• Developed strong foundations in Python for data analysis, including data cleaning, manipulation, and visualization using libraries such as Pandas, NumPy, and Matplotlib.
• Performed data cleaning and preprocessing on real-world datasets to prepare them for analysis and modeling.
• Used Excel for building dashboards, applying formulas, PivotTables, and performing exploratory data analysis (EDA).
• Completed hands-on projects involving data extraction, transformation, and reporting, improving analytical and problem-solving skills.
• Applied statistical concepts to interpret data trends and create actionable insights.
• Created data visualizations to clearly present findings to non-technical audiences.
• Worked with structured datasets to practice predictive modelling (linear regression, classification basics).
• Collaborated on assignments simulating real workplace scenarios such as generating reports, summarizing insights, and presenting solutions.

Master's in Data Science – University of East London (2024 – 2025)

Bachelor's in B.com – Jyoti Nivas College Autonomous (2020 – 2023)