Nama Rajkumar

Data Science

https://www.opentalent.in/nama-rajkumar

Data Science with 1+ years in Machine Learning, AI, and Python.

Key Strengths

Strong academic background in Computer Science and Engineering (Data Science).
Extensive project experience in key Data Science and AI domains, including LLMs, RAG, Time-Series Forecasting, and traditional Machine Learning.
Proficiency in Python and relevant libraries/frameworks (LangChain, HuggingFace, PyTorch, TensorFlow, Scikit-learn, XGBoost, Pandas).
Demonstrated ability to design and implement end-to-end data science pipelines, from preprocessing to deployment.
Experience with vector databases (Pinecone) and web application deployment (Flask, Streamlit) for AI solutions.
Achieved high accuracy in forecasting models and strong performance in LLM fine-tuning tasks.
Awarded 2nd place in a GenAI Hackathon, indicating practical problem-solving skills and innovation.

Skill Analysis

Data Scientist — Artificial Intelligence

★★★★★

94%

The candidate scored 94% on the 'Data Scientist — Artificial Intelligence' exam, indicating a very strong grasp of the subject matter and related skills.

Data ScienceArtificial IntelligenceMachine LearningDeep LearningNatural Language ProcessingTime Series AnalysisModel DeploymentRAGLLMs

Cultural & Operational Fit

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.

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Projects

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.

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.

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.

Certifications

Database Design

Oracle Academy

June 1, 2026 – Present

Altair Data Science Master

Altair RapidMiner

June 1, 2026 – Present

Database Programming with SQL

Oracle Academy

June 1, 2026 – Present

Key Strengths

Strong academic background in Computer Science and Engineering (Data Science).
Extensive project experience in key Data Science and AI domains, including LLMs, RAG, Time-Series Forecasting, and traditional Machine Learning.
Proficiency in Python and relevant libraries/frameworks (LangChain, HuggingFace, PyTorch, TensorFlow, Scikit-learn, XGBoost, Pandas).
Demonstrated ability to design and implement end-to-end data science pipelines, from preprocessing to deployment.
Experience with vector databases (Pinecone) and web application deployment (Flask, Streamlit) for AI solutions.
Achieved high accuracy in forecasting models and strong performance in LLM fine-tuning tasks.
Awarded 2nd place in a GenAI Hackathon, indicating practical problem-solving skills and innovation.

Skill Analysis

Data Scientist — Artificial Intelligence

★★★★★

94%

The candidate scored 94% on the 'Data Scientist — Artificial Intelligence' exam, indicating a very strong grasp of the subject matter and related skills.

Data ScienceArtificial IntelligenceMachine LearningDeep LearningNatural Language ProcessingTime Series AnalysisModel DeploymentRAGLLMs

Cultural & Operational Fit

Cultural Fit Analysis

Soft Skills & Operational Fit

Nama Rajkumar

Key Strengths

Skill Analysis

Data Scientist — Artificial Intelligence

Cultural & Operational Fit

About

Top Skills

Skills

Education

Projects

Certifications

Key Strengths

Skill Analysis

Data Scientist — Artificial Intelligence

Cultural & Operational Fit