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Data Science with less than a year in Machine Learning & Data Analysis
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Highly motivated and results-oriented Data Science student with a strong academic record (CGPA: 3.98/4.0) and practical experience in data analysis, machine learning, and programming. Proficient in Python, R, SQL, and various ML/DL frameworks. Demonstrated ability to lead projects, organize technical events, and implement solutions in areas like seizure detection, fraud detection, and spam classification. Eager to apply analytical and critical thinking skills in a data-driven environment.
Institute of Management Sciences (IMSciences)
Bachelor of Science (BS) · Data Science
October 1, 2022 – June 1, 2026
Google Developer Groups on Campus (IMSciences)
Core Team Member & Women Techmakers Lead
October 1, 2024 – Present
India
YoungDev
Machine Learning Intern
June 1, 2024 – July 1, 2024
India
Pinnacle Full-Stack Interns
Data Science Intern
April 1, 2024 – May 1, 2024
India
Color Detection using OpenCV and Python
June 1, 2026 – Present
• Developed a tool to detect and display RGB values from images in real-time. • Addressed challenges like color profile discrepancies, for example Redwood RGB variations. • Key Learnings: Studied the impact of compression artifacts on color accuracy and improved calibration.
Heart Disease Prediction
June 1, 2026 – Present
• Developed a machine learning model to predict heart disease using Random Forest Classifier. • Conducted exploratory data analysis (EDA) and feature engineering to improve prediction accuracy. • Achieved 74.26% accuracy, identifying key medical indicators influencing heart disease risk.
Email Spam Detection
June 1, 2026 – Present
• Implemented text preprocessing and feature extraction using TF-IDF vectorization. • Trained a Decision Tree Classifier achieving 97% accuracy in classifying emails as spam or non-spam. • Evaluated model performance using precision, recall, and F1-score metrics.
Credit Card Fraud Detection
June 1, 2026 – Present
• Built a fraud detection system for credit card transactions. • Achieved 99.99% accuracy in detecting fraudulent transactions with high precision and recall scores. • Preprocessed and visualized transactional data to uncover fraud patterns.
Text Data Analysis
June 1, 2026 – Present
• Processed textual data using NLTK, TF-IDF, and Bag of Words techniques. • Implemented n-grams and stopword removal to improve feature extraction. • Visualized insights using Seaborn and Matplotlib.
EEG-Based Seizure Detection Using Machine Learning
June 1, 2026 – Present
• Designed a model to detect epileptic seizures from EEG signals. • Applied signal preprocessing techniques including channel selection and downsampling, and extracted key features from time-series data. • Trained Random Forest, Decision Tree, Hard Voting, and Stacking classifiers to differentiate between seizure and non-seizure states, achieving exceptional performance.
Academic Integrity Violation Detection Using ML
June 1, 2026 – Present
• Integrated and cleaned multi-source educational data including registrations, assessments, and VLE logs into a unified dataset. • Engineered features such as engagement consistency, submission timing, and score-to-interaction ratios to uncover suspicious patterns. • Trained and evaluated models to flag potentially dishonest behavior. • Implemented K-means clustering to identify four distinct engagement profiles, isolating high-risk “high-score/low-engagement" students.
Retail Analysis
June 1, 2026 – Present
• Conducted an in-depth analysis of customer behavior and purchase trends in an online retail dataset. • Performed RFM analysis for customer segmentation including Loyal, At-Risk, and Average Customers. • Applied the Apriori algorithm to discover frequent itemsets and seasonal sales patterns.
Data Analysis with R Programming
June 1, 2026 – Present
McKinsey Forward Program - Critical Thinking, Problem-Solving, Leadership, Communication
McKinsey & Company
June 1, 2026 – Present
Introduction to SQL
DataCamp
June 1, 2026 – Present
Preprocessing for Machine Learning in Python
DataCamp
June 1, 2026 – Present
Business Communication & AI for Professionals
RoshanKalAcademy x LUMS
June 1, 2026 – Present
What is Data Science?
IBM
June 1, 2026 – Present
Understanding Data Engineering
DataCamp
June 1, 2026 – Present
Understanding Data Science
DataCamp
June 1, 2026 – Present
Cultural Fit Analysis
The candidate's involvement in Google Developer Groups and Women Techmakers initiatives highlights a proactive, community-oriented mindset and a commitment to diversity and inclusion. The breadth of academic projects across various domains (healthcare, finance, education, retail) suggests adaptability and a willingness to tackle diverse challenges. This indicates a good cultural fit for an organization that values continuous learning, collaboration, and impact.
Soft Skills & Operational Fit
The candidate demonstrates strong analytical thinking, critical thinking, leadership, and team collaboration skills through their project work and involvement in Google Developer Groups. Their ability to organize technical events and promote women in tech indicates good communication and initiative. The McKinsey Forward Program certification further supports their critical thinking and problem-solving abilities, which are crucial for operational fit in a senior role.