PRANAYA KUMAR DASH
Backend Architecture · Scalable APIs · Database Optimization
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MCA graduate specialising in AI and ML. I've cut DB calls by 50% on a live e-commerce platform, fixed race conditions in production with transaction.atomic(), and reduced dashboard load times by 66% through composite indexing. Currently building Cliniq.ai.
Custom, high-performance web applications built with Python/Django and modern front-end technologies for seamless user experiences.
Robust RESTful APIs designed for scalability, security, and seamless integration between complex systems and front-end portals.
Advanced schema optimization and data modeling using PostgreSQL and MySQL to ensure data integrity and rapid query performance.
Crafting fluid, mobile-first interfaces that look stunning and perform flawlessly across all devices and screen resolutions.
AI-driven SaaS platform for healthcare management, optimizing clinic workflows and patient data processing.
Scalable peer-to-peer car rental marketplace connecting individual fleets with verified peer renters under secure KYC flows.
Premium luxury car booking ecosystem. Race condition eliminated with transaction.atomic() during concurrent booking windows.
Full-stack e-commerce platform. Achieved 50% reduction in DB calls via query optimisation for high-traffic environments.
Performance-focused task management. Achieved 66% faster dashboard loads via composite indexing.
Voice-enabled personal assistant with custom task automation and context-aware query resolution using advanced LLMs.
Intelligent bookmarking tool that organizes and manages web resources with ease, enhancing daily browsing productivity.
Commercial web platform for a security agency featuring service portfolios and inquiry management for private security services.
Currently refining full-stack expertise with Python and scalable architecture.
Specialized in Software Development, Database Management, and Web Technologies
Developed strong analytical and problem-solving skills.
Intensive professional training focusing on end-to-end application development, database management, and Python-based microservices.
Accuracy Sentiment Model
Implemented using Logistic Regression & Naive Bayes
Ready to discuss your next system architecture or data-driven prototype?