Implemented CNN based architecture models(ResNet, VGGNet) for object classification problems.

Implemented YOLO algorithm for applying in retail domain - Customer Behavior Analysis, Foot Analytics, Inventory stock analysis.

Built deep learning pipeline leveraging pytorch, torchvision docker containers.

Combined POS database with customer data to derive business KPs

Presented science recommendations on retail analytics based on computer vision technologies - Monitoring store traffic (at various customer touch points), Curbside pickup monitoring.

As the sole developer on the project, assumed full responsibility for leading the engineering strategy and making technology decisions independently, ensuring efficient and effective project execution.

Proactively seeking feedback and input from the executive team and reflecting in the in the product Frontend.

Understanding the design needs and goals for the product and proactively meeting the deadlines.

Collaborated closely with the design team to understand design needs and project goals, facilitating seamless integration of design elements into the product.

Demonstrated strong time management skills by effectively prioritizing tasks and managing time to meet project deadlines, resulting in the delivery of high-quality design work on schedule.

Designed and engineered enterprise-level microservice Bluecom.ai application, an AI-powered e-commerce tool for seamless multi-channel management

Integrated multiple third-party systems, increasing the customer experience by 12% in the MVP

Optimized and automated business logic for the core marketing experiments, including A/B, Auto Targeting, and multi-variant testing.