Commercial & Investment Bank - Automated Trading Strategies AI\ML Researcher - Associate

JPMorgan Chase & Co.; City of Westminster; On-site; GBP 65,000 - 90,000; Full time

Job summary

A leading financial institution in the UK is seeking an Associate AIML Researcher to join their Automated Trading Strategies team. This role involves applying cutting-edge AIML methods to enhance systematic trading strategies and direct engagement in model development and production activities. You will have the independence to drive impactful research and collaborate closely with data and engineering teams, ensuring your contributions have a profound impact on trading performance. Prior finance knowledge is not required, encouraging candidates with diverse backgrounds in technology and research to apply.

Qualifications

• Strong experience in AIML model development and application.
• Proficient in machine learning and deep learning research.
• Strong engineering skills and knowledge of multiple programming languages.

Responsibilities

• Apply AIML model to find predictive patterns from large datasets.
• Integrate prediction model into existing trading strategies.
• Contribute to team's AIML libraries and production systems.

Skills

AIML model application

Machine learning and deep learning research

Engineering skills

Python proficiency

Java/C++/C# proficiency

Tools

PyTorch

TensorFlow

Job description

Job Summary

The Automated Trading Strategies (ATS) group is responsible for systematic trading across FX, Rates, Commodities, and Credit markets. The team is responsible for a broad scope including the design and implementing of cutting edge proprietary quantitative models that drive our automated trading systems (pricing, risk management and execution), the oversight of day-to-day risk and operations, and the optimization Franchise client liquidity offering in a data-driven manner. As an Associate AIML Researcher within the Automated Trading Strategies team, you will accelerate our efforts on applying the latest AIML methods on systematic trading strategy R&D. As part of a small focused team with minimal bureaucracy, you will have great independence to pursue the research directions you think would be most impactful. You are enabled with enough computational resources, and supported by excellent data and engineering teams to realize your vision. Your work will be deployed directly into production trading with P&L responsibility. The field is complex and often requires creative problem-solving, but it's also a great chance to learn and grow professionally. You will be responsible for improving every part of our models: from featurization of data, to architecture design, to training dynamics, to how trading decisions are made. You will be part of a fast-growing effort and have the opportunity to have a holistic view of market making & exchange trading, including alpha generation, portfolio construction/optimization and trade execution algorithms. This position does not require prior finance knowledge or experience. Candidates with experience in technology, AI or research institutions are strongly encouraged to apply.

Job Responsibilities

• Apply AIML model to find predictive pattern from large dataset
• Integrate prediction model into existing strategies or set up a new one
• Contribute to team's AIML libraries as well as production algo system
• Experience in machine learning and deep learning research for any domain
• Relevant experience using frameworks such as PyTorch, TensorFlow or equivalent
• Strong engineering skills valued, efficiency in other languages (Java/C++/C#) beyond Python
• Experience solving complex problems and comparing alternative solutions, tradeoffs, and different perspectives to determine a path forward