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AI Engineer with less than a year in Python and Data Science.
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
AI and Machine Learning fresher with strong foundational knowledge in Python, statistics, and machine learning algorithms. Skilled in data pre-processing, exploratory data analysis (EDA), model building, and evaluation using libraries such as NumPy, Pandas, and Scikit-learn. Eager to apply analytical and problem-solving skills in an entry-level AI/ML role.
State Board of Technical Education & Training
Diploma of Technolgy
N/A – June 30, 2023
Jawaharlal Nehru Technological University
Bachelor of Technology
N/A – June 30, 2026
Board of secondary Education
Secondary Education
N/A – May 31, 2019
Resume-Driven Interview Question Generator
June 21, 2026 – Present
Developed an AI-based resume analysis system using Python and NLP, automating interview question generation with 90% relevance based on extracted skills. Implemented resume text extraction supporting 2 file formats (PDF and DOCX) using PyPDF2 and python-docx, enabling accurate parsing of candidate data. Designed an NLP preprocessing pipeline using spaCy and NLTK to clean text and identify 20+ technical skills from resumes. Generated skill-based technical interview questions by mapping extracted skills to a predefined dataset of 50+ questions, improving interview readiness. Built a Streamlit web application with real-time resume upload and results display, reducing manual screening effort by 60%.
Singapore Resale Flat Price Prediction
June 21, 2026 – Present
Built a machine learning regression model to predict Singapore HDB resale flat prices using 10,000+ historical housing records. Performed data cleaning, pre-processing, and feature engineering on 15+ features using Pandas and NumPy, improving data quality and consistency. Conducted Exploratory Data Analysis (EDA) with 20+ visualizations using Matplotlib and Seaborn to identify key price-influencing factors. Split the data into training and testing sets and evaluated a Decision Tree Regression model using Scikit-learn, achieving an R² score above 0.80 and reduced MAE. Serialized and saved the validate model using Pickle, enabling 100% reusable deployment for real-world price prediction use cases.
Wine Fraud Detection
June 21, 2026 – Present
Developed a Support Vector Machine (SVM) model to perform data prediction and classification, achieving ~85-90% accuracy on test data. Preprocessed datasets by handling 100% missing values, performing feature selection, and applying data normalization to improve model performance. Trained and evaluated the SVM model using Python and Scikit-learn with multiple kernel configurations to optimize prediction results. Assessed model performance using key metrics including accuracy, precision, recall, and confusion matrix, improving classification reliability by ~20%. Applied the model to real-world structured datasets containing 1,000+ records, supporting data-driven decision-making.
Data Science With GEN-AI
Medha Edu Tech
June 1, 2026 – Present
Cultural Fit Analysis
The candidate's projects are all academic and heavily focused on core AI/ML tasks, which aligns well with an AI Engineer role. The diversity of projects (NLP, regression, classification) shows a broad interest within the AI domain. However, the lack of professional experience or diverse team projects limits the assessment of cultural fit beyond technical alignment.
Soft Skills & Operational Fit
The candidate's project descriptions indicate an ability to work on structured problems and apply learned concepts. The focus on academic projects suggests a learning-oriented individual. However, without professional experience or psychometric test results, it's difficult to assess stress handling, team collaboration, or work attitude.