VP of AI/ML Data Science — Payments Innovation

JP Morgan Chase; Greater London; Vor Ort; GBP 140.000 - 210.000; Vollzeit

Zusammenfassung

J.P. Morgan is seeking a Vice President Machine Learning Data Scientist in Payments to lead design, development, and production deployment of ML applications, including generative AI, on cloud infrastructure.

You will own end-to-end delivery, mentor engineers, and translate complex technical work into clear outcomes for stakeholders. You will partner with product, operations, risk, and technology teams to drive data-led transformations, establish reusable ML capabilities, and ensure reliability,

Qualifikationen

• Master's 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.

Aufgaben

• 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.

Kenntnisse

Machine learning

Generative AI

Python

ML Ops

LLMOps

Distributed systems

Cloud AWS

Stakeholder management

Mentoring

Ausbildung

Master's degree in quantitative field

Tools

PyTorch

TensorFlow

scikit-learn

NumPy

pandas

Jobbeschreibung

J.P. Morgan is seeking a Vice President Machine Learning Data Scientist in Payments to lead design, development, and production deployment of ML applications, including generative AI, on cloud infrastructure.

You will own end-to-end delivery, mentor engineers, and translate complex technical work into clear outcomes for stakeholders. You will partner with product, operations, risk, and technology teams to drive data-led transformations, establish reusable ML capabilities, and ensure reliability,