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Data Science with 1+ years in Machine Learning, AI, and Python.
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Highly motivated Data Science professional with a strong foundation in Machine Learning, AI, and Python. Experienced in developing AI-powered solutions, natural language processing models, and time-series forecasting. Proven ability to build scalable data pipelines, optimize model accuracy, and deploy web applications. Seeking to leverage technical skills and project experience in a challenging data-driven role.
CVR College of Engineering
B.Tech · Computer Science and Engineering (Data Science)
November 1, 2022 – June 1, 2026
Sri Chaitanya Junior College
Intermediate · 12th Standard
May 1, 2020 – May 1, 2022
Fitness Assistant
December 1, 2024 – June 1, 2026
Engineered an AI-powered fitness assistant using LangChain and Gemini-2.0-Flash LLM. Built a scalable document processing and retrieval pipeline using embedding-based search and intelligent text chunking, ensuring accurate and efficient information access within RAG workflows. Integrated a vector database to enable low-latency semantic search and deployed a Flask-based web application, delivering real-time personalized fitness insights and an enhanced user experience.
Natural Language to SQL Query Generator
December 1, 2024 – June 1, 2026
Developed an AI-powered Text-to-SQL model using the Spider dataset, translating natural language questions into executable SQL queries with schema linking and serialization. Fine-tuned a T5-base model with LoRA for efficient domain-specific learning on limited GPU resources, achieving strong Exact Match and Execution Accuracy. Designed an end-to-end workflow for preprocessing, fine-tuning, validation, and inference, enabling reproducible results and easy deployment.
Car Production Demand Forecasting
December 1, 2024 – June 1, 2026
Designed a hybrid ensemble forecasting model integrating SARIMA, XGBoost, and LSTM to predict daily car production while accounting for seasonality, holidays, and non-linear patterns. Implemented an automated pipeline covering data preprocessing, feature engineering, model training, validation, and performance visualization. Optimized forecast accuracy R2 scores, achieving over 90% accuracy and enhanced demand stability.
Agriculture Crop Yield Prediction and Crop Recommendation
December 1, 2024 – June 1, 2026
Designed and implemented supervised machine learning algorithms for crop prediction and yield forecasting. Performed extensive EDA, data preprocessing, and feature engineering to enhance model quality, followed by hyperparameter tuning for optimal performance.
Database Design
Oracle Academy
June 1, 2026 – Present
Database Programming with SQL
Oracle Academy
June 1, 2026 – Present
Altair Data Science Master
Altair RapidMiner
June 1, 2026 – Present
The candidate scored 94% on the 'Data Scientist — Artificial Intelligence' exam, indicating a very strong grasp of the subject matter and related skills.
Strengths
Cultural Fit Analysis
The candidate's academic projects demonstrate a strong interest and hands-on experience in diverse areas of Data Science and AI, aligning well with an innovative and research-oriented culture. The participation in a GenAI Hackathon suggests a proactive and collaborative spirit. The breadth of technologies used across projects indicates adaptability and a willingness to learn new tools. The target role of 'Data Science' is a direct match for the candidate's educational background and project portfolio.
Soft Skills & Operational Fit
The candidate's project descriptions indicate a structured approach to problem-solving and an ability to work on complex, multi-faceted projects. The academic achievements suggest diligence and a strong work ethic. While the psychometric test score is moderate (280/500), it provides some insight into logical reasoning and work attitude, but further assessment would be beneficial for a comprehensive understanding of soft skills and operational fit.
Limitations