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Data Science with less than a year in Machine Learning and NLP
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Aspiring Data Scientist with 4 months of internship experience in data collection, preprocessing, exploratory analysis, and model development using Python and R. Worked on a movie recommendation system and Netflix data analysis, and completed NLP training. Certified in Data Science, Machine Learning, and Tableau, with strong analytical skills and a passion for solving real-world problems through data-driven solutions.
Madanapalle Institute of Technology and Science
Master of Computer Applications
August 1, 2019 – June 30, 2022
Sri Srinivasa Degree College
Bachelor of Science · MPCs
August 1, 2016 – June 30, 2019
Krishna Reddy Siddhartha Junior College
Intermediate · MPC
June 1, 2014 – May 31, 2016
Sri Shirdi Sai High School
SSC
June 1, 2013 – May 31, 2014
Unified Mentor
Data Science Intern
December 1, 2024 – January 31, 2025
India
Worksbot Applications Private Limited
Data Scientist Internship
February 1, 2022 – April 30, 2022
India
Machine Failure Prediction Using IoT Sensor Data and Machine Learning
February 1, 2026 – March 31, 2026
Developed a machine failure prediction model using IoT sensor data in Python, applying the complete data science lifecycle including EDA, preprocessing, outlier handling, and feature engineering. Built and optimized a Random Forest predictive maintenance model with SMOTE for imbalanced data, achieving 97% accuracy and improved failure detection performance. Implemented a cloud-based data pipeline using AWS S3 and performed statistical analysis and visualization using Pandas, NumPy, Matplotlib, and Seaborn.
Netflix Data Cleaning Analysis and Visualization
December 1, 2024 – January 31, 2025
Performed data cleaning, preprocessing, and exploratory data analysis (EDA) on a Netflix dataset with 8,790 records, identifying trends in content distribution by country, genre, and release year. Developed interactive data visualizations using Pandas, Matplotlib, and Seaborn to analyze content trends, ratings distribution, and growth of movies and TV shows on Netflix. Built a Random Forest Classifier to predict content type (Movie vs TV Show), achieving 70.3% accuracy through hyperparameter tuning and feature engineering.
View ProjectPet Classification Model Using CNN
April 1, 2023 – May 31, 2023
Developed a Convolutional Neural Network (CNN) using TensorFlow to classify pet images into cats and dogs, handling images with varying sizes and lighting conditions. Designed and trained a multi-layer CNN architecture (convolution, pooling, dense, and dropout layers) to improve image feature extraction and classification accuracy. Evaluated model performance by training for multiple iterations (100, 200, 300 epochs) and analyzing accuracy and loss metrics on test data.
Natural Language Processing
Internshala
May 1, 2025 – Present
Masters Program-Data Scientist
Simplilearn in collaboration with IBM
July 1, 2023 – Present
Cultural Fit Analysis
The candidate's project diversity (IoT failure prediction, Netflix analysis, pet classification, movie recommendation, NLP spam detection) shows a broad interest in different data science applications. This breadth, combined with certifications in NLP and a Master's program in Data Science, indicates a proactive learning attitude. The remote internship experiences suggest adaptability. However, the overall experience level is junior, which might not align with a senior role requiring extensive industry experience and mentorship capabilities.
Soft Skills & Operational Fit
The candidate's project descriptions indicate an ability to work through complex data problems and apply various analytical and machine learning techniques. The internship experiences suggest a capacity for structured learning and project execution. However, the limited professional experience (internships only) means operational fit in a senior role requiring independent decision-making and leadership is yet to be fully demonstrated.