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Entry-level AI Engineer with Python and Machine Learning skills
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Computer Science graduate with hands-on project experience in Python, Data Analysis, and Machine Learning. Looking to apply programming and analytical skills in an entry-level technology role and gain practical experience in software and data-driven development.
IIIT-Bangalore
Executive Diploma · Data Science and AI
August 1, 2025 – June 30, 2026
Vasavi College of Engineering
B.E. · Computer Science
August 1, 2018 – June 30, 2022
Narayana Junior College
Intermediate
June 1, 2015 – May 31, 2017
Credit Card Fraud Detection using ML
June 25, 2026 – Present
Built a Python-based fraud detection system with Pandas and Scikit-learn on 1M+ transactions, using SMOTE for class imbalance, Stratified K-Fold cross-validation, and Logistic Regression, Random Forest, and Gradient Boosting models for fraud classification. Built a Gradient Boosting Classifier model achieving a recall of 82% and accuracy of 95%
View ProjectWaste Segregation using CNN
June 25, 2026 – Present
Built a CNN-based waste classification system achieving high accuracy in categorizing waste into 7 classes. Preprocessed and trained on a dataset of multi-class waste images, improving classification reliability. Reduced manual waste sorting effort by automation segregation using AI
View ProjectAI Data Analyst Agent(LLM powered System)
June 25, 2026 – Present
Developed an LLM-powered data analyst agent using Python and Pandas to convert natural language into executable code for automated analysis and insights, with a model-agnostic architecture supporting local and API-based LLMs for scalable deployment. Implemented prompt engineering, validation, error handling, and retry mechanisms for reliable execution; currently enhancing with Streamlit-based UI and data visualization.
View ProjectCultural Fit Analysis
The candidate's projects are primarily academic, focusing on core AI/ML applications. This aligns well with a role requiring strong technical fundamentals in AI. The diversity of projects (fraud detection, image classification, LLM agent) shows a broad interest within AI. However, the lack of professional experience or collaborative projects makes it challenging to fully assess cultural fit in a team-oriented, fast-paced environment.
Soft Skills & Operational Fit
The candidate's project descriptions indicate an ability to work on complex problems and a structured approach to development (e.g., implementing validation, error handling, retry mechanisms). The academic nature of projects suggests a learning-oriented mindset. However, without professional experience, it's difficult to assess operational fit, teamwork, or stress handling capabilities.