Applied AI/ML Scientist — Market Operations Automation

Testing Site - JPMC; Greater London; Hybrid; GBP 70,000 - 110,000; Full time

Job summary

JPMorgan Chase in London seeks an Applied AI & ML Scientist to design, develop, and deploy AI/ML solutions that enhance Market Operations. You will collaborate with business stakeholders and tech partners to translate pain points into scalable AI-driven tools that improve efficiency and accuracy.

The role emphasizes hands-on model development, production deployment, and ongoing optimization while staying current with the latest AI/ML advancements.

Qualifications

• Degree in data science, computer science or related field, or equivalent experience.
• Strong foundation in AI/ML concepts and practical data analysis skills.
• Experience with large datasets and statistical analysis.
• Hands-on experience training, deploying, and maintaining models in production.
• Proficiency in Python and libraries like TensorFlow, PyTorch, scikit-learn.

Responsibilities

• Develop and deploy advanced ML models for operational challenges.
• Build AI/ML tools for automation, anomaly detection, and workflow optimization.
• Architect generative AI applications to automate business processes.
• Monitor model performance and optimize production systems.
• Collaborate with stakeholders to translate requirements into solutions.
• Document methodologies, results, and best practices for knowledge sharing.
• Stay current with AI/ML advancements and apply them to problems.

Skills

AI/ML concepts

Python

ML libraries

MLOps

Generative AI

LLMOps

Cloud platforms

Data analysis

Statistical analysis

Production deployment

Communication

Education

BSc/MSc in Data Science, CS, AI

PhD in Data Science, CS, AI

Tools

TensorFlow

PyTorch

scikit-learn

MLOps tools

LLMOps tools

AWS

GCP

Azure

Job description

JPMorgan Chase in London seeks an Applied AI & ML Scientist to design, develop, and deploy AI/ML solutions that enhance Market Operations. You will collaborate with business stakeholders and tech partners to translate pain points into scalable AI-driven tools that improve efficiency and accuracy.

The role emphasizes hands-on model development, production deployment, and ongoing optimization while staying current with the latest AI/ML advancements.