I'm M.sc Data Science student at the Chandigarh University, and hold a B.Sc. (Hons.) Statistics from Delhi University. My acdemic background has given me a strong foundation in statistical reasoning, data analysis, and computational methods.

I am deeply interested in transforming complex datasets into meaningful insights using analytics, visualization, and machine learning. My work focuses on building reliable, interpretable models that support data-driven decision-making across domains such as healthcare, fraud detection, and business analytics.

I approach data science as both analytical and story-telling discipline - where numbers are translated into insights that matter.

• 📊 Exploratory Data Analysis & Data Storytelling :- Conducting in-depth EDA on real-world datasets to identify trends, anomalies, and actionable insights using Python-based visualization techniques.
• 🤖 Machine Learning Models :- Developing supoervised and unsupervised learning models for classification and regression problems, with emphasis on feature engineering, model evaluation, and interpretability.
• 📈 Statistical Analysis and Hypothesis Testing :- Applying probability theory, inferential statistics and regression analysis to validate assumptions and support analytical conclusions.
• 🧠 Foundations of Deep Learning :- Building conceptual & practical understanding of neural networks and CNNs using TensorFlow/Keras through guided experimentation.

Python | R | SQL | C | SPSS | HTML

Supervised & Unsupervised Learning | Regression | Classification | Ensemble Methods | SVM | KNN | Neural Networks (TensorFlow/Keras)

Data Cleaning | Feature Engineering | Pipelines | Database Design | API Integration (basic)

Power BI | Matplotlib | Seaborn | ggplot2 | Data Storytelling

Probabilty Theory | Hypothesis Testing | Expperimental Design | Correlation & Regression Analysis

Jupyter Notebook | Google Colab | Git | Excel Analytics | Cloud Fundamentals

• Build reproducible, well-documented data science projects.
• Strengthen research readiness through statistical and ML experimentation.
• Collaborate on open-source and applied analytics work.

• Machine Learning and Applied Data Science
• Statistical Modelling & inference-driven analytics
• Deep Learning & data Storytelling
• Predictive Modelling and risk/fraud Detection Analysis
• Healthcare and public-sector data analysis
• Time Series Analysis and Forecasting
• Explainable AI and Model Interpretability (Foundational)

📧 Email :- vanshika.statistics@gmail.com

👔 LinkedIn :- linkedin.com/in/vanshika

💻 GitHub :- github.com/vanshika-data-lab

🏆 Kaggle :- kaggle.com/vanshika

✨ Every dataset holds a story. My goal is to uncover it, model it responsibly, and communicate it clearly through data.