Data Science with less than a year in Machine Learning & Data Analysis.
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Results-driven Data Scientist with expertise in Machine Learning, Predictive Modeling, and Data Analysis. Proficient in Python, TensorFlow, and Scikit-Learn with a strong foundation in statistical modeling and data-driven problem solving. Experienced in building RAG-based AI systems and healthcare prediction models, focusing on feature engineering, model optimization, and performance improvement. Skilled in transforming complex datasets into actionable insights through advanced analytics and effective data visualization techniques.
Greater Noida Institute of Technology (GNIOT)
Bachelor of Technology · Electronics and Communications Engineering
November 1, 2021 – July 1, 2025
TechSaksham (Microsoft & SAP Initiative)
AI Intern
January 1, 2025 – February 1, 2025
India
RAG-Based AI Teaching Assistant
June 1, 2026 – Present
• Built an end-to-end Retrieval-Augmented Generation (RAG) pipeline to transcribe course audio using Whisper and generate structured semantic embeddings. • Implemented a context-aware query system using vector similarity search to retrieve relevant content and generate accurate responses using LLM. • Designed a fully automated multi-stage pipeline (audio to embeddings to response) enabling scalable ingestion of new learning content. • Optimized retrieval efficiency using vector embeddings stored as Joblib objects, improving response relevance and system performance.
California Housing Price Prediction
June 1, 2026 – Present
• Built an end-to-end regression pipeline including data preprocessing, feature engineering, encoding, and scaling using Scikit-learn. • Trained and evaluated models such as Linear Regression, Decision Tree, and Random Forest using cross-validation techniques. • Selected Random Forest model based on lowest RMSE and improved prediction accuracy through hyperparameter tuning. • Developed a production-ready inference pipeline with automated preprocessing and model persistence using Joblib.
Introduction to Data Science
Cisco Networking Academy
February 1, 2026 – Present
Data Science Certification
Code With Harry
January 1, 2025 – Present
Cultural Fit Analysis
The candidate's projects demonstrate a strong interest in practical applications of data science, including predictive modeling and AI assistants. The internship with TechSaksham (Microsoft & SAP Initiative) shows an inclination towards industry-relevant work. The diversity of projects (housing price prediction, RAG system, multi-disease classification) suggests adaptability and a broad interest in data science domains. However, the experience level is very junior, which might require significant mentorship in a senior role.
Soft Skills & Operational Fit
The candidate's project descriptions indicate an ability to work on complex, multi-stage pipelines, suggesting good problem-solving and project management skills. The focus on end-to-end solutions implies a results-driven approach. However, without direct interaction or psychometric test results, assessing stress handling, teamwork, and communication clarity in a collaborative setting is challenging.