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Pulkit C. Python, Web3 and Financial Platforms

My name is Pulkit C. and I have over 5 years of experience in the tech industry. I specialize in the following technologies: Python, MetaTrader 4, MetaTrader 5, Flask, Forex Trading, etc.. I hold a degree in Bachelor of Technology (BTech). Some of the notable projects I’ve worked on include: Automated Options Trading Dashboard for NSE F&O, Custom Strategy Backtester for Algorithmic Trading, Scalable Copy Trading Architecture IBKR API & Multi-Account Support, IBKR Breakout Scanner – Python-Based Automated Trade Execution, Strategy Backtesting with Backtest.py—Python Trading Simulation Tool, etc.. I am based in Bareilly, India. I've successfully completed 14 projects while developing at Softaims.

I am a business-driven professional; my technical decisions are consistently guided by the principle of maximizing business value and achieving measurable ROI for the client. I view technical expertise as a tool for creating competitive advantages and solving commercial problems, not just as a technical exercise.

I actively participate in defining key performance indicators (KPIs) and ensuring that the features I build directly contribute to improving those metrics. My commitment to Softaims is to deliver solutions that are not only technically excellent but also strategically impactful.

I maintain a strong focus on the end-goal: delivering a product that solves a genuine market need. I am committed to a development cycle that is fast, focused, and aligned with the ultimate success of the client's business.

Main technologies

  • Python, Web3 and Financial Platforms

    5 years

  • Python

    4 Years

  • MetaTrader 4

    4 Years

  • MetaTrader 5

    1 Year

Additional skills

  • Python
  • MetaTrader 4
  • MetaTrader 5
  • Flask
  • Forex Trading
  • PyCharm
  • Data Science
  • C++
  • Solidity
  • Web3
  • QuickFIX
  • Fix Documentation
  • Financial Trading
  • Online Financial Trading
  • TradingView

Direct hire

Potentially possible

Previous Company

Oracle Financial Services Software

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Experience Highlights

Automated Options Trading Dashboard for NSE F&O

Developed a custom trading dashboard that integrates with a broker’s API to identify Iron Condor strategies among NSE F&O stocks. The system fetches real-time market data, applies selection criteria, and automatically places orders based on account margin. Additionally, I implemented a Net Position Panel where users can monitor live positions with PnL (Profit & Loss) tracking and instantly square off individual or all positions. This solution provided my client with a seamless automated trading workflow, improved decision-making, and reduced manual intervention.

Custom Strategy Backtester for Algorithmic Trading

I built a custom backtesting engine that lets traders and quants easily validate and optimize strategies. Users can select datasets, choose from pre-built strategies or code their own, and get detailed CSV reports after every run. This project highlights my expertise in algorithmic trading, automation, and dashboard development, helping traders test ideas faster, reduce risk, and scale effectively. I also build custom backtesting solutions, dashboards, and automation tailored to client needs.

Scalable Copy Trading Architecture IBKR API & Multi-Account Support

The client needed a scalable and reliable copy trading system integrated with Interactive Brokers (TWS). I designed and developed a backend solution using Django (FastAPI optional), enabling centralized management of multiple client accounts. The system supports real-time trade copying with position scaling, TradingView/Python webhook integrations, and includes risk management controls. The solution helped the client test strategies via paper trading and prepared them for live deployment.

IBKR Breakout Scanner – Python-Based Automated Trade Execution

This project is a Python-based breakout scanner integrated with Interactive Brokers (IBKR) for demo purposes. It scans a predefined list of symbols and executes trades when the current LTP exceeds the previous close price by a configurable percentage. The bot is limited to one trade per symbol per day and is highly configurable via a JSON config file. A help file is included to guide users on setup, usage, and strategy adjustment. This modular demo showcases my ability to build scalable, real-time execution systems.

Strategy Backtesting with Backtest.py—Python Trading Simulation Tool

This project showcases a Python-based backtesting framework using Backtest.py, designed to simulate and evaluate custom trading strategies. It helps traders and developers test strategies on historical data, visualize performance, and optimize key parameters before going live. Features include strategy scripting, performance metrics, stop loss/take profit logic, and real-time charting. Ideal for anyone building or validating algo trading systems.

Education

  • Graphic Era University

    Bachelor of Technology (BTech) in Computer science

    2013-01-01-2017-01-01

Languages

  • English
  • Hindi

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