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Data Science with less than a year in Machine Learning & NLP
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Data Analyst specializing in Machine Learning and NLP with experience building end-to-end predictive systems and deploying scalable AI solutions. Skilled in transforming raw data into actionable insights, with proven project experience in churn prediction, time-series forecasting, and NLP-based applications.
Vel Tech University
Bachelor of Technology · Computer Science Engineering (CSE)
January 1, 2020 – May 1, 2024
Stock Price Prediction System using LSTM
December 1, 2025 – April 1, 2026
Developed an end-to-end stock price prediction system using LSTM (Deep Learning), leveraging real-time data from Yahoo Finance API; performed data preprocessing, normalization (MinMaxScaler), and implemented time-series modeling using a 60-day sliding window to accurately forecast next-day closing prices. Engineered a modular pipeline for data extraction, feature engineering, model training, and prediction, optimized hyperparameters to improve model performance, and visualized actual vs predicted trends using Matplotlib for better decision insights.
Customer Churn Prediction
February 1, 2025 – July 1, 2025
Built a Customer Churn Prediction model using machine learning, achieving 85% accuracy through exploratory data analysis, feature engineering, and model validation on 200K+ customer records. Developed automated Power BI dashboards to monitor churn metrics, reducing manual reporting time by 70% and supporting data-driven customer retention strategies.
Fake News Detection System
December 1, 2023 – May 1, 2024
Developed a Fake News Detection System using NLP and multi-class classification, achieving 89% precision by processing and analyzing 50K+ news articles with feature engineering and ensemble modeling techniques. Deployed the model using Docker-based containerization with a web interface, incorporating feature importance analysis to improve prediction accuracy and model interpretability.
Sentiment Analysis System
January 1, 2023 – May 1, 2023
Developed a Sentiment Analysis system using NLP techniques (tokenization, lemmatization, text pre-processing) and fine-tuned a BERT model, achieving 92% classification accuracy on social media data. Built and deployed a Flask-based REST API capable of handling 1000+ real-time requests per hour, along with data visualization dashboards to monitor sentiment trends and support data-driven insights.
Data Science for Everyone
Reliance Foundation Skilling Academy
June 1, 2026 – Present
Python for Data Science
Saylor Academy
March 1, 2026 – Present
Cultural Fit Analysis
The candidate's academic projects cover a good range of data science applications (NLP, time-series, churn prediction), indicating a broad interest in the field. The use of various tools and frameworks (Scikit-learn, TensorFlow, PyTorch, Keras, Docker, Flask, FastAPI, Power BI) suggests adaptability and a willingness to learn new technologies. The target role of 'Data Science' aligns well with the project experience. However, the lack of professional experience means cultural fit is primarily inferred from academic pursuits.
Soft Skills & Operational Fit
The candidate's project descriptions indicate an ability to work on complex problems and deliver end-to-end solutions. The focus on deployment and real-time systems suggests a practical, results-oriented approach. However, without direct work experience or psychometric test results, it's difficult to assess stress handling, team collaboration, or other soft skills.