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AI Engineer with less than a year in Data Analysis & Generative AI
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Assessing your cultural and operational fit
AI/ML Engineer with hands-on experience designing and deploying intelligent, scalable solutions across diverse domains. Proficient in Python, Machine Learning, Deep Learning, Natural Language Processing (NLP), and Generative AI. Experienced in developing and fine-tuning Large Language Models (LLMs), Prompt Engineering, and building autonomous AI Agents. Skilled in working with SQL databases. AI-driven business solutions through effective cross-functional collaboration.
CIPET-IPT, Chennai
Bachelor of Engineering (BE) · Manufacturing Engineering
August 1, 2021 – June 30, 2025
Christ king Girls Hr. Sec. School, Chennai
Higher Secondary Certificate (HSC)
June 1, 2019 – May 31, 2021
Christ king Girls Hr. Sec. School, Chennai
Secondary School Leaving Certificate (SSLC)
N/A – May 31, 2019
PSCS Analytics Pvt Ltd
Data Analyst Intern
May 1, 2026 – Present
Chennai, Tamil Nadu, India
Sentiment Analysis using Generative AI
June 23, 2026 – Present
Created a sentiment analysis application to evaluate customer opinions and feedback trends. Developed an NLP-based sentiment analysis system to classify customer sentiments from reviews as positive, negative, and neutral. Generated analytical insights by identifying feedback patterns to support data-driven business decision-making. Improved customer experience strategies through actionable sentiment trends and automated text classification. Tools Used: Python, Transformers, Hugging Face, Deep Learning.
Customer Segmentation
June 23, 2026 – Present
Used K-Means to segment customers based on purchase behavior. Analyzed RFM metrics and visualized clusters for business insights. Helped identify high-value and at-risk customer groups.
Image Classification Using Deep Learning (Cats vs Dogs)
June 23, 2026 – Present
Developed a deep learning model using Convolutional Neural Networks (CNN) to classify images of cats and dogs. The model was trained on a labeled dataset to accurately distinguish between the two classes. Built a CNN model for binary image classification (Cats vs Dogs). Performed image preprocessing, resizing, and normalization. Applied data augmentation to improve model generalization. Trained and evaluated the model using accuracy and loss metrics. Achieved effective classification performance on test images. Dataset: Cats vs Dogs Dataset (Kaggle). Tools Used: Python, TensorFlow, Keras, CNN, NumPy, Matplotlib, Kaggle Dataset.
House Price Prediction System
June 23, 2026 – Present
Developed a machine learning model to predict house prices based on location, size, and amenities using regression algorithms. Performed data cleaning and feature engineering. Built and optimized regression models for accurate prediction. Analyzed housing data trends and model performance. Developed a simple prediction interface using Flask. Tools Used: Python, Scikit-learn, Pandas, NumPy, Linear Regression, Random Forest, Flask.
Fake News Detection Using NLP
June 23, 2026 – Present
Built an NLP-based machine learning model to classify news articles as fake or real using text processing and classification techniques. Performed text preprocessing (tokenization, stopword removal). Converted text to features using TF-IDF. Trained Logistic Regression model for classification. Evaluated model using accuracy metrics. Dataset: Kaggle Fake and Real News Dataset. Tools Used: Python, NLP, NLTK, Scikit-learn, TF-IDF, Pandas, Logistic Regression.
E-Commerce Delivery Prediction
June 23, 2026 – Present
Built a classification model to predict if products will be delivered on time. Performed data cleaning, feature selection, and model comparison. Identified key factors like product weight, cost, and customer service calls.
Data Science & AI Developer Training
Boston Business Solutions
June 1, 2025 – Present
Cultural Fit Analysis
The candidate's academic projects demonstrate a strong interest and foundational skill set in AI/ML, which aligns well with an AI Engineer role. The diversity of projects (e-commerce prediction, customer segmentation, image classification, fake news detection, house price prediction, sentiment analysis) indicates a broad curiosity and willingness to explore different applications of AI. The inclusion of Generative AI projects and training shows an awareness of current trends. However, all projects are academic, and the only work experience is a Data Analyst internship, which is less directly aligned with a senior AI Engineer role's typical responsibilities. This suggests a good foundational fit but a need for more practical, industry-level experience.
Soft Skills & Operational Fit
The candidate lists communication, leadership, interpersonal, and team collaboration as soft skills. While these are valuable, there is no direct evidence from the provided data (e.g., project descriptions or work experience) to assess their operational fit or how these skills are applied in a professional setting. The internship as a Data Analyst involved reporting and data analysis, which would require some communication, but the depth is not clear.