Internship – Backend Developer
2 weeks ago
Location: India (Bhubaneswar) & Remote option available
Domain: Algorithmic / High-Frequency Trading (HFT)
Type: Internship (3–6 months, with potential full-time conversion)
JarNox is building the next-generation trading infrastructure to power algorithmic and high-frequency strategies across global markets. As an intern, you’ll gain hands-on exposure to quantitative trading, backend system design, and financial data engineering, working directly with experienced developers and quants.
- Support the design and development of automated trading strategies across asset classes.
- Assist in building and maintaining backend systems for data ingestion, APIs, and execution frameworks.
- Contribute to back-testing, statistical analysis, and real-time monitoring of strategies.
- Work with large market datasets to identify patterns, inefficiencies, and trading opportunities.
- Learn and help implement risk management tools for position sizing and exposure monitoring.
- Stay updated with market structure, regulations, and technology influencing trading efficiency.
- Education: Pursuing or recently completed a degree in Computer Science, Engineering, Mathematics, Statistics, or a Finance-related field.
- Programming: Strong skills in Python (knowledge of C++/R is a plus).
- Foundations: Understanding of data structures, algorithms, and probability/statistics.
- Preferred:
- Familiarity with trading platforms, APIs, or market data systems.
- Exposure to quantitative models or back-testing frameworks.
- Mindset:
- Curious, analytical, and comfortable working with data.
- Able to collaborate in cross-functional teams (developers, researchers, quants).
- Eagerness to learn, iterate, and adapt in fast-paced environments.
- Real-world exposure to algorithmic trading and backend systems.
- Mentorship from experienced quants, engineers, and traders.
- Opportunity to work on live trading infrastructure in simulation environments.
- Internship stipend (performance-linked).
- Potential for a full-time offer based on performance.
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