Data Scientist with 3+ years of experience sniffing out insights from massive datasets, wielding Python, Java, SQL, and data analysis tools like a seasoned pro. Skilled in computer vision and deep learning frameworks, I'm passionate about uncovering hidden patterns that unlock Improved ROI. Let's chat about how I can help you make data-driven decisions that boost your bottom line!
Led the development of a vision system integrating YOLOv8 and UNet segmentation models to achieve precise clothing dismantling and optimize downstream processes.
Leveraged AWS SageMaker to build scalable image classification pipelines using TensorFlow. Implemented distributed training across multiple instances for improved efficiency.
Implemented advanced data augmentation techniques, resulting in a 10% improvement in IoU score for the semantic segmentation model, showcasing expertise in enhancing data quality and accuracy.
Developed and built ETL and data augmentation pipelines, to expand dataset by 30% and achieve a 12% lift in model accuracy due to improved generalization.
Developed ready to use garment processing pipeline for efficient workflow integrated with vision system.
Deployed a vision system prototype, configuring industrial grade cameras and lighting and establishing TCP/IP network communication for seamless integration with a control system.
Developed performant CNN models for automobile part categorization (98.2% on 10k+ images, using OpenCV). Demonstrated expertise in techniques with broad AI applications, including image processing and transfer learning.
Boosted automobile part classification accuracy by 73% by fine-tuning an Inception v3 model (TensorFlow), demonstrating skill in transfer learning for rapid solution development.
Implemented a Siamese Network for similarity learning, combining distance metrics and statistical analysis techniques. Achieved 98% accuracy on out-of-training data, significantly improving model generalization.
Developed a multi-stage ETL pipeline for object detection/classification for a sustainable remanufacturing vision system, reducing manual inspection time by 30% and boosting object classification accuracy by 10%.
Enhanced ML pipeline efficiency through targeted research and experimentation (A/B testing, Bayesian optimization). Built clear data visualizations (Tableau, Power BI) to convey model behavior and drive improvements, presented to senior leadership. (Project Demo)
Deployed 100+ email campaigns for brands like Estée Lauder and MAC Cosmetics using Salesforce Marketing Cloud, delivering an average click-through rate of 25%.
Developed automated test suites (Python, Selenium) for web applications, reducing manual testing effort by 24% and accelerating release cycles.
Built API test automation scripts to validate functionality and data integrity. Increased test coverage by 25% for core back-end services.
Performed SQL queries to extract and analyze user behavior data from Adobe Analytics.
Analyzed and worked with customer data for audience segmentation and targeting, for 50+ email marketing campaigns.
Hackathons: Eventify-U | A web application that alerts college students’ to nearby activities and provides personalized event recommendations based on an individual’s interests and past participation, using Python and machine learning.