Data Scientist in training ,skills in Python, SQL, ML, and visualization
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Healthcare_ML_Project
April 22, 2026 – Present
This repository implements a Healthcare Machine Learning Pipeline designed to automate the full lifecycle of data preparation, model training, and deployment. The system centralizes healthcare data in a PostgreSQL database, ensuring maintainability and consistency across workflows.
View ProjectAdaptive_Learning_Platform
April 9, 2026 – Present
Adaptive_Learning_Platform — repository
View ProjectTravel_and_Tourism_RAG_System
April 1, 2026 – Present
AI-powered tourism question answering system using RAG
View ProjectKmeans
March 31, 2026 – Present
A practical approach to uncovering patterns using K-Means clustering
View ProjectCustomer_Lifetime_Value_Prediction
February 22, 2026 – Present
Customer_Lifetime_Value_Prediction — repository
View ProjectSales_Performance_and_Decision_Making
February 7, 2026 – Present
This folder contains the complete end-to-end statistical analysis of retail sales performance, examining the effectiveness of marketing campaigns on revenue generation.
View ProjectIris_Dataset-
January 26, 2026 – Present
Performed unsupervised clustering on the Iris dataset using K-Means. Applied Min–Max scaling, determined optimal cluster count using the Elbow Method, and visualized cluster separation. Demonstrated end to end ML workflow including pre-processing, model selection, and interpretation.
View ProjectCultural Fit Analysis
The candidate's projects primarily revolve around data science and machine learning, which aligns with a Data Scientist role. The diversity of project topics (healthcare, retail, tourism, general ML) suggests a broad interest within the field. However, the lack of team-based projects or professional experience makes it difficult to assess collaboration or broader cultural fit.
Soft Skills & Operational Fit
Insufficient data to assess soft skills and operational fit. The candidate's project descriptions indicate a focus on technical implementation.