Freelancers using Python in Chennai

Freelancers using Python in ChennaiFreelancers using Python in Chennai

Projects People

Algo Trading Developer - Pine Script,MQL5 &Python Automation

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Algo Trading Developer - Pine Script,MQL5 &Python Automation

Cover image for Designed and implemented a robust

Designed and implemented a robust webhook-based trading automation system that connects TradingView signals to real-time trade execution via the Tradovate API. The system is built using Python and handles signal reception, validation, and order execution in a seamless automated pipeline. The architecture ensures low-latency communication, secure data handling, and reliable execution of trades without manual intervention. It processes incoming webhook alerts, applies validation logic, and triggers precise API-based trade execution. Key features include: • Real-time webhook signal processing (TradingView alerts) • Python-based signal receiver and validation engine • Secure and reliable API integration (Tradovate) • Low-latency execution pipeline • Fully automated trade workflow (zero manual input) • Scalable design for multi-strategy integration This solution is ideal for traders and firms looking to automate their strategies using webhook-driven architecture, enabling faster execution, reduced human error, and consistent performance in live trading environments.

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Cover image for Developed a fully automated trading

Developed a fully automated trading system for MetaTrader 5 (MT5) that executes trades based on validated multi-indicator signals. The system integrates TradingView-generated signals with a Python-based processing engine, which evaluates multiple technical conditions before triggering precise trade execution. The Expert Advisor (EA) is designed with advanced trade logic, risk management, and real-time execution capabilities. It ensures consistent performance by removing emotional decision-making and strictly following predefined rules. Key features include: • Automated trade execution on MT5 (buy/sell orders) • Integration with external signal sources (TradingView via webhook) • Multi-indicator validation (RSI, EMA, ADX, Volume, etc.) • Built-in risk management (lot sizing, SL/TP control) • Real-time processing with minimal latency • Fully customizable strategy logic This system enables traders to automate their strategies end-to-end — from signal generation to execution — ensuring speed, accuracy, and consistency in live market conditions.

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Cover image for Engineered a high-performance Python-based trading

Engineered a high-performance Python-based trading signal engine designed to generate precise and reliable trade signals using multi-indicator confluence logic. The system evaluates over 12 technical indicators including RSI, EMA, ADX, Volume, and trend-based conditions to identify strong market opportunities while effectively filtering out noise and false signals. The architecture is built to process real-time market data, validate multiple conditions simultaneously, and trigger only high-probability trade setups. This significantly improves signal accuracy and reduces unnecessary trades. Key capabilities include: • Multi-indicator confluence engine (12+ conditions) • Real-time signal processing and validation • False signal reduction using layered logic • Scalable architecture for integration with trading APIs • Seamless compatibility with automated execution systems (webhooks, APIs) This system can be integrated with platforms like TradingView, Tradovate, or custom trading environments to enable fully automated trading workflows — from signal generation to execution. Designed for traders and firms looking to achieve consistent, rule-based, and emotion-free trading through intelligent automation.

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Cover image for Built a complete end-to-end automated

Built a complete end-to-end automated trading system that captures alerts from TradingView, processes them through a Python-based webhook engine, validates multi-condition logic, and executes trades directly via the Tradovate API — eliminating manual intervention and improving execution speed and accuracy.

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Aditya Mohapatra

ML & Data Science | IIT Madras Graduate

ML & Data Science | IIT Madras Graduate

Cover image for Random walk scaling on networks

Random walk scaling on networks

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Waste Segregation CNN

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Cover image for Web Scrapping and NLP

Web Scrapping and NLP

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Thananjayan Rajasekaran

Expert QA Engineer | Automation & Test Ops Guru

Expert QA Engineer | Automation & Test Ops Guru

Cover image for Test Scripting to Monitoring

Test Scripting to Monitoring

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k6: Live streaming of results and monitoring

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Cover image for Java-Based Testing Frameworks for Software Quality Assurance

Java-Based Testing Frameworks for Software Quality Assurance

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Fullstack Developer, Certified DevOps Engineer

Fullstack Developer, Certified DevOps Engineer

Cover image for ohitsmeMohit/Song-recommender-System

ohitsmeMohit/Song-recommender-System

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Portfolio Website

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KimtVak8143/ClimateActionPlanner

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Senior Software Engineer

Senior Software Engineer

Cover image for Power up your customer support with Zendesk

Power up your customer support with Zendesk

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Cover image for Signet Jewelers - Signet Jewelers | Home

Signet Jewelers - Signet Jewelers | Home

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IDFC FIRST BANK

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Pixel-Perfect Fullstack Engineer

Pixel-Perfect Fullstack Engineer

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Faculty Leave Management System

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Cover image for DebugMaster: A Competitive Debugging Event Platform

DebugMaster: A Competitive Debugging Event Platform

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Human Anatomy AR VR

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proChennai, India

Full-Stack Developer & Data Engineer | AI-Augmented Delivery

Full-Stack Developer & Data Engineer | AI-Augmented Delivery

Cover image for I built Fileflip - an

I built Fileflip - an

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Cover image for Palettify — Website Color Extractor
Extract

Palettify — Website Color Extractor Extract

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Cover image for Built a production-ready SaaS analytics

Built a production-ready SaaS analytics

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I built TaskMelt — AI-powered

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AWS FinOps expert cutting cloud costs for 7 years

New to Contra

AWS FinOps expert cutting cloud costs for 7 years

Cover image for Delivered $1.3M+ AWS savings in

Delivered $1.3M+ AWS savings in 2025 through strategic FinOps initiatives including EC2 rightsizing, Savings Plans optimization, Reserved Instances, EBS cleanup, S3 optimization, and continuous governance across 200+ AWS accounts.

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Cover image for Designed and implemented an AWS

Designed and implemented an AWS cost dashboard for 200+ accounts to provide centralized spend visibility, service-wise breakdown, monthly trends, forecasting, and business-unit level reporting. Replaced manual Excel reporting with automated, interactive analytics dashboards.

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Cover image for EC2 and EBS rightsizing assessment

EC2 and EBS rightsizing assessment focused on reducing waste and improving cloud efficiency. Analyzed CPU, memory, storage utilization, IOPS, and throughput to identify oversized instances, underutilized volumes, and cost-saving opportunities without impacting performance.

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Cover image for AWS FinOps automation solution built

AWS FinOps automation solution built using Python and cloud reporting tools to streamline cost management processes. Implemented automated billing reports, anomaly alerts, tagging compliance checks, savings trackers, and executive dashboards for real-time AWS spend visibility and continuous optimization.

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