Eesha Sheikh

Architected scalable trading applications using React, Next.js, TypeScript, Node.js, Python, and PostgreSQL, supporting real-time market analysis and intelligent investment workflows. Built responsive trading UIs including candlestick charts, technical indicators, watchlists, order workflows, portfolio analytics, and live market updates. Developed secure backend services using Node.js, FastAPI, and Go for market data, analytics, authentication, user preferences, and AI-generated trading insights. Integrated predictive ML models via versioned inference APIs for price forecasting, volatility analysis, anomaly detection, and sentiment scoring. Delivered real-time updates using WebSockets, Kafka, and Redis Streams while maintaining responsiveness during peak market activity. Designed PostgreSQL/TimescaleDB/MongoDB schemas for ticks, candles, portfolios, transactions, model outputs, and user configurations. Improved chart rendering and frontend responsiveness using virtualization, memoizati

Architected scalable trading applications using React, Next.js, TypeScript, Node.js, Python, and PostgreSQL, supporting real-time market analysis and intelligent investment decision workflows. Built responsive trading interfaces including candlestick charts, technical indicators, watchlists, order workflows, portfolio analytics, and live market updates across desktop and mobile. Developed secure backend services with Node.js, FastAPI, and Go for market data, analytics, authentication, user preferences, and AI-generated trading insights. Integrated predictive machine-learning models via versioned inference APIs for price forecasting, volatility analysis, anomaly detection, and sentiment scoring. Implemented real-time delivery using WebSockets, Kafka, and Redis Streams. Designed PostgreSQL/TimescaleDB/MongoDB schemas for ticks, candles, portfolios, transactions, model outputs, and user trading configurations. Improved frontend performance via virtualization, memoization, incremental upda

Built data-intensive web applications using React, Next.js, Node.js, Python, PostgreSQL, and MongoDB supporting real-time analytics and personalized customer experiences. Developed reusable React components for dashboards, data grids, and interactive charts with responsive and accessible UI patterns. Designed REST and GraphQL services for application data, analytics, user management, subscriptions, notifications, and secure third-party integrations. Integrated machine-learning models and analytical pipelines for recommendations, forecasting, classification, scoring, and automated interpretation of complex datasets. Implemented streaming features with Kafka, Redis, WebSockets, and asynchronous workers to improve data freshness during traffic spikes. Optimised Node.js and Python services via profiling, caching, async execution, connection pooling, query tuning, and efficient serialization, reducing API latency by 39%. Built secure identity workflows (JWT/OAuth, RBAC, encryption, validati