Applied AI/ML Data Scientist, Vice President

Salary: £62,000 - 102,000 per year

Requirements

• Masters degree in a quantitative field, or equivalent practical experience
• Deep understanding of machine learning fundamentals with strong applied data analysis skills
• Demonstrated experience designing rigorous evaluation and measurement in real-world settings
• Demonstrated experience deploying and operating machine learning models in production at scale, including monitoring, drift and performance management, reliability, incident management, and continuous improvement
• Strong Python software engineering skills, including modular object-oriented design, testing, performance tuning, and debugging
• Working knowledge of MLOps and LLMOps and distributed systems, including training and serving patterns, batch versus real-time architectures, feature stores, orchestration, and scalable data processing
• Ability to design intrinsic and extrinsic evaluations aligned with business goals, including offline and online alignment and guardrails for unintended outcomes
• Experience working in regulated environments with awareness of model risk, controls, privacy and security, and audit-ready documentation
• Strong stakeholder management and teamwork skills, with the ability to drive outcomes in partnership with cross-functional teams
• Experience with NLP and generative AI, including large language models, retrieval-augmented generation, tool and function calling, agentic workflows, multi-agent orchestration, and related evaluation and safety patterns
• Familiarity with agentic building blocks and standards, including orchestration frameworks, context and memory management, and interoperability protocols such as MCP
• Experience with machine learning frameworks and data science packages such as PyTorch, TensorFlow, scikit-learn, NumPy, pandas, SciPy, and statsmodels
• Experience deploying to AWS, including services such as SageMaker and Bedrock, and operating production large language model and machine learning workloads with attention to cost, latency, performance, security, and scaling
• Experience integrating human-in-the-loop and user feedback signals into iterative improvement, including active learning, preference signals, and labeling strategies

Responsibilities

• Lead end-to-end delivery of machine learning and AI solutions for complex payments and banking operations problems, from discovery and framing to production rollout and lifecycle management
• Develop innovative machine learning solutions, including generative AI and multi-agent approaches, and define evaluation, safety, and monitoring strategies for production use
• Own production deployment patterns including containerization, continuous integration and delivery, automated testing, model and prompt registries, model and version governance, monitoring and alerting, and rollback strategies
• Architect and deploy scalable, reliable, and secure machine learning and large language model services integrated with strategic platforms and downstream consumers across APIs, batch, streaming, and event-driven patterns, meeting service level objectives
• Partner with product, operations, risk and control, and technology teams to influence roadmaps, align on requirements, and deliver data-led transformations
• Establish reusable, modular data science and machine learning capabilities that scale across use cases, including feature engineering, evaluation harnesses, prompt tooling patterns, agent frameworks, orchestration, and context and memory management
• Provide technical leadership and mentorship through code reviews, design reviews, best practices, and upskilling across data science and engineering partners
• Communicate with technical and non-technical stakeholders, translating model outputs into decisions, tradeoffs, and operational plans
• Maintain strong documentation for approaches, model cards, runbooks, and operational procedures

Technologies

• AI
• AWS
• Architect
• Incident Management
• Support
• Machine Learning
• MCP
• MLOps
• PyTorch
• Python
• Security
• TensorFlow
• numpy
• pandas
• Cloud

More

We are J.P. Morgan, a global leader in financial services and the Commercial & Investment Bank, serving corporations, governments, wealthy individuals, and institutional investors in more than 100 countries. We provide strategic advice, raise capital, manage risk, and extend liquidity across banking, markets, securities services, and payments. We value diversity and inclusion, support reasonable accommodations, and offer a collaborative, first-class environment where our people are our strength. This is a full-time role, posted on 2026-08-28.

last updated 36 week of 2026