About the Role:
Quantitative skills are at the core of J.P. Morgan’s capabilities, contributing critically to the competitiveness and innovating power of our firm. The team's mission is to develop and maintain sophisticated mathematical models, cutting-edge methodologies and infrastructure to improve the performance of algorithmic trading strategies and promote advanced electronic trading solutions to our clients worldwide.
We are seeking individuals passionate in areas such as machine learning, reinforcement learning, deep learning, computational statistics, and applied mathematics with a keen interest to apply these techniques to the financial field and have a transformational impact to the business.
On top of electronic trading, we also work closely with trading desks to develop statistical arbitrage strategies and provide data-driven solutions to their business processes such as recommendation engines, flow categorization and clustering, and inventory optimization.
Roles and responsibilities include the following:
- Developing mathematical models for equities electronic trading algorithms using methodologies such as Reinforcement Learning, neural networks, time-series forecasting, clustering methods, dimensionality reduction methods (PCA, Kernel methods, …).
- Designing and developing analytics for consumption in our trading engine or for optimization of our business processes.
- Supporting trading activities by explaining model and algorithm behavior, carrying out scenario analyses, developing and delivering quantitative tools, and supporting analytics including transaction cost analysis
- Engaging in direct client interaction to promote and market our algorithms
The ideal candidate will have:
- Earned a MS, PhD or equivalent degree program in computer science, machine learning, math, statistics, econometrics, physics, chemistry, operations research, financial engineering.
- Publications or experience in machine learning, AI, computer vision, optimization, computer science, statistics, applied mathematics, or data science.
- 8+ years experience designing and developing electronic trading models and supervising their end-to-end integration.
- Strong software design and development skills using Python and Java (or C++).
- Exceptional analytical, quantitative and problem-solving skills, as well as the ability to communicate complex research in a clear and precise manner.
- Ability to manipulate and analyze complex, large scale, high-dimensionality data from varying sources
- Mastered advanced mathematics and statistics (i.e., probability theory, time series, econometrics)
- Experience writing trading algorithms from a quantitative perspective, and some exposure to volume, volatility prediction modeling, market impact modeling, portfolio and single stock optimization is a plus.
Req #: 180034856