Machine Learning - Internship

About the internship:Seeking a 'nerd' Quantitative Trading Intern with Python programming skills and craze for technical analysis. You will translate trading strategies from TradingView PineScript into modular Python code, execute rigorous historical backtests, and deploy strategies into live/paper trading environments via OpenAlgo and broker APIs.

Key Responsibilities

Script Conversion: Translate PineScript strategies and custom indicators (such as Pivot SuperTrend, ATR stops, and dynamic pivot levels) into clean, vectorized Python code using pandas, numpy, or numba.

Backtesting & Optimization: Build and execute backtests on multi-year historical data. Calculate core strategy metrics including Sharpe ratio, max drawdown, win rate, profit factor, and trade frequency.

Live Market Testing: Set up forward/paper trading environments to evaluate real-time strategy performance, latency, and signal reliability under actual market conditions.

Execution & API Integration: Connect Python strategy engines to OpenAlgo and broker APIs (e.g., Zerodha Kite, Angel One, Fyers) using Webhooks or REST endpoints.

Risk Management: Account for real-world execution friction such as slippage, transaction costs, order placement logic, and trailing stop adjustments.Who can apply:Only those candidates can apply who:are available for full time (in-office) internshipcan start the internship between 11th Sep'26 and 16th Oct'26are available for duration of 1 monthhave relevant skills and interests* Women wanting to start/restart their career can also apply.Stipend:INR₹ 10,000 - 15,000 /monthDeadline:[hidden]:59:59Other perks:Letter of recommendation, Flexible work hours, 5 days a week, Free snacks & beveragesSkills required:Data Analytics, Stock Trading and Python LibrariesOther Requirements:Required QualificationsSome mathematics / quant with strong fundamentalsStrong proficiency in Python with experience in data manipulation libraries (pandas, numpy).Working knowledge of TradingView PineScript (v4 or v5) and technical analysis concepts.Familiarity with backtesting tools or frameworks (e.g., backtesting.py, Backtrader, VectorBT, or custom Pandas loops).Understanding of Webhooks, REST APIs, and JSON structure for automated signal execution.Basic understanding of equities, futures, or options trading mechanics.About Company:The Indian Institute of Technology, Bombay (IITB) is one of the fifteen higher institutes of technology in the country set up with the objective of making facilities available for higher education, research, and training in various fields of science and technology. With the same mission and vision, Prof. Ganesh Ramakrishnan is gearing up to take rural India a leap ahead. For his outstanding contributions, he has also been awarded the IBM Faculty Award 2011.

Responsibilities

Seeking a 'nerd' Quantitative Trading Intern with Python programming skills and craze for technical analysis. You will translate trading strategies from TradingView PineScript into modular Python code, execute rigorous historical backtests, and deploy strategies into live/paper trading environments via OpenAlgo and broker APIs.

Key Responsibilities

Script Conversion: Translate PineScript strategies and custom indicators (such as Pivot SuperTrend, ATR stops, and dynamic pivot levels) into clean, vectorized Python code using pandas, numpy, or numba.

Backtesting & Optimization: Build and execute backtests on multi-year historical data. Calculate core strategy metrics including Sharpe ratio, max drawdown, win rate, profit factor, and trade frequency.

Live Market Testing: Set up forward/paper trading environments to evaluate real-time strategy performance, latency, and signal reliability under actual market conditions.

Execution & API Integration: Connect Python strategy engines to OpenAlgo and broker APIs (e.g., Zerodha Kite, Angel One, Fyers) using Webhooks or REST endpoints.

Risk Management: Account for real-world execution friction such as slippage, transaction costs, order placement logic, and trailing stop adjustments.