Join J.P. Morgan’s Quantitative Trading & Research (QTR) team, a recognized leader in quantitative trading, financial engineering, statistical modeling and portfolio management. As an Associate/Vice President in Quantitative Trading & Research for Equity e Trading, you will play a key role in developing sophisticated models and methodologies for optimal execution, collaborating with colleagues, product owners, marketers, and risk managers to deliver innovative electronic trading solutions globally.

As an Associate/Vice President in Quantitative Trading & Research (QTR) team for Equity e Trading, you will be contributing to the enhancement of our algorithmic execution strategies. You will develop new, advanced quantitative models as well as analysing and improving existing models. You will work closely with Electronic Client Services and trading desks to tailor models, iterate based on experimentation and client feedback, and translate research into measurable performance improvements.

Job Responsibilities:

• Analyze large, multi-horizon datasets (tick, intraday, daily) to extract stable causal relationships and signal structures.
• Evaluate, document, and back‑test methodologies to ensure robustness, reproducibility, and performance under varying market regimes.
• Lead the development of analytics and data-driven processes to automate and optimize model calibrations.
• Validate production implementations for fidelity with the original research specifications.
• Propose A/B experiments to test hypotheses.
• Partner with the Electronic Client Service desk to design and enhance algorithmic trading strategies.
• Support diagnosis of trading decisions by explaining model and algorithm behavior, conducting scenario analyses, and developing quantitative tools and data analytics.
• Collaborate with global teams to share best practices and drive continuous improvement in electronic trading.

Required Qualifications, Capabilities, and Skills:

• Master’s or PhD in a quantitative discipline (e.g., Computer Science, Physics, Machine Learning, Mathematics, Statistics, Operations Research).
• Relevant experience in quantitative research, electronic trading, or related fields.
• Advanced knowledge of mathematics and statistics (probability theory, time series, econometrics, causal inference).
• Exceptional analytical, quantitative and problem-solving skills to break down complex high dimensional decision variable problems into smaller tractable subproblems.
• Experience handling and analyzing time-series data.
• Proven ability to condense and communicate complex research ideas clearly and precisely, both in writing and verbally.
• Strong software design and development skills using Python.

Preferred Qualifications, Capabilities, and Skills:

• Experience with algorithmic execution strategies.
• Knowledge of cash equity markets, microstructure and market impact.
• Experience with alpha research.
• Experience with kdb+/q.
• Experience with efficient and scalable compute, cloud infrastructure.
• Experience solving stochastic optimization problems.
• Skilled in client engagement and presenting technical concepts to non-technical audiences, with familiarity in machine learning and deep neural networks.