Data Analyst Role

The J.P. Morgan interview process typically starts with a timed online aptitude test, followed by one or two technical rounds focusing on Python, data structures, and basic quantitative concepts. The final HR round assesses cultural fit, communication skills and motivation. Candidates should practice coding on platforms like LeetCode and be ready to discuss data‑analysis projects or internships.

J.P. Morgan promotes a high‑performance culture that balances rigorous analytical work with strong mentorship and learning opportunities. Employees enjoy structured career progression, global mobility options and a supportive environment that values work‑life balance and diversity.

Bachelor's or Master's degree in Computer Science, Computer Engineering, Electrical Engineering, Mathematics or related field; minimum 60% aggregate (or CGPA 6.0/10); final year students or fresh graduates of 2025/2026 batch; no active backlogs at the time of joining; strong programming foundation in Python; good communication and teamwork skills.

Round 1: Online aptitude & logical reasoning test → Round 2: Technical interview (Python, data structures, system design, KDB basics) → Round 3: HR interview (fit, motivations, behavioral questions)

J.P. Morgan, a 200‑year‑old global financial powerhouse, operates across investment banking, commercial banking, asset management and payments. In India, the firm is known for its strong culture of meritocracy, continuous learning and a commitment to diversity and inclusion. Employees benefit from exposure to world‑class clients, cutting‑edge technology platforms and a collaborative environment that encourages innovative thinking. The Commercial & Investment Bank division, where this role sits, drives capital markets, risk management and trading solutions for corporations, governments and institutional investors worldwide. The Analyst – Commodities Systematic Trading role is a gateway for fresh engineering or computer‑science graduates to dive into the fast‑moving world of systematic commodities trading. You will be embedded within a cross‑market systematic team that blends alpha generation, electronic trading, data science and machine learning. Your day‑to‑day will involve building and maintaining robust tools, user interfaces and frameworks that enable traders to take disciplined risk in commodities markets. You will also contribute to systematic strategy development, performance monitoring and attribution, while processing, cleaning and analysing massive datasets that feed research pipelines. Key responsibilities include: 1. Design, develop and support Python‑based tools and dashboards for systematic risk taking. 2. Implement and maintain performance monitoring and attribution systems for commodity strategies. 3. Enhance integration of models and tools across asset‑class teams. 4. Clean, transform and analyse large historical and real‑time datasets. 5. Collaborate closely with traders to understand workflow gaps and propose improvements. 6. Participate in the development and back‑testing of systematic strategies. 7. Ensure code quality, version control (Git) and documentation standards. 8. Contribute to the migration of legacy data pipelines to modern platforms. 9. Provide ad‑hoc analytical support for market research and risk reporting. 10. Stay updated on emerging technologies, data‑science libraries and commodity market trends. The tech stack revolves around Python (NumPy, pandas, dash, panel), KDB/Q for time‑series data, Git for source control and cloud‑based data pipelines. Successful analysts can expect a clear growth path: from analyst to associate, then to senior associate or quantitative researcher, with opportunities to lead product teams or move into trader‑focused roles. Joining J.P. Morgan offers unparalleled mentorship, exposure to global markets and a platform to build a high‑impact career in systematic trading.