Alina Lakra

I’m a Data Analyst and aspiring Data Scientist who turns messy data into clear decisions. In my work, I combine exploratory data analysis, machine learning, and business intelligence to help teams move from insight to action with confidence.

During my Data Science internship at WiseAnalytics, I conducted EDA on retail customer datasets to profile behavior, detect anomalies, and assess data quality across 10+ features. I then engineered high-impact features such as trend score, competitor pricing index, and discount sensitivity to strengthen predictive performance.

I built and trained a Random Forest Classifier using Scikit-learn to predict customer acceptance of personalized offers, and I used SHAP to deliver interpretable, explainable AI insights. I also developed a personalized offer recommendation engine to support targeted marketing campaigns, and I presented findings to non-technical managers using visualizations and plain-language summaries.

My project work reflects the same goal: make advanced analytics usable. I created an AI-powered Data Analyst Assistant in Streamlit that automates EDA and supports clustering, regression, and anomaly detection through a natural language interface, and I built an NLP-based Social Media Sentiment Analysis dashboard to classify sentiment and visualize results for non-technical users.