About the Internship
Selected intern's day-to-day responsibilities include:1. Translate researched models into production-ready code using Python, ensuring seamless integration with trading APIs and executable logic for algorithmic strategies across equities, derivatives, and crypto.
2. Set up and optimize execution pipelines, including real-time data feeds, order management systems, and latency-sensitive components to support high-frequency or systematic trading.
3. Perform routine system health checks, debug issues, and implement automated alerts for performance anomalies, ensuring 99%+ uptime for deployed strategies.
4. Build and maintain ETL processes for ingesting, cleaning, and storing market data from APIs (e.g., Polygon, Bloomberg), enabling efficient access for backtesting and live updates.
5. Assist in running simulations on historical data to verify executable strategies, calculating key metrics like Sharpe ratio and drawdown while incorporating real-world costs.
6. Develop reusable code templates and Jupyter notebooks for teaching live execution concepts, helping participants simulate data management and deployment processes.
7. Work with the team to iterate on data storage solutions (e.g., SQL/NoSQL databases) and cloud-based monitoring tools, documenting processes for scalability.
Number of Openings
2 openingsPerks of this Internship
Certificate Recommendation letter Informal dress code
Other Requirements
1. are available for full time (in-office) internship
2. have relevant skills and interests
3. can start the internship between 25th Jan'26 and 1st Mar'26
4. are available for duration of 6 months
5. have already graduated or are currently in any year of study
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