Data Scientist Lead (Fraud Strategy & Analytics) – Chase UK / J.P. Morgan | London

Chase UK (J.P. Morgan) is hiring a Data Scientist Lead for its Fraud Strategy & Analytics team in London. Requires a Master’s in a STEM field and experience in fraud/financial crime.

About the Company: Enterprise Scale Meets Fintech Agility

J.P. Morgan is a premier global financial services firm trusted by the world’s most prominent corporations, governments, institutional investors, and individual consumers. Operating under the foundational philosophy of doing “first-class business in a first-class way,” the firm combines century-long regulatory stability with massive investments in technological innovation to build secure, world-scale products.

As part of J.P. Morgan’s International Consumer Bank expansion, Chase UK has fundamentally reshaped the mobile banking landscape since its launch. Operating as a fast-paced, startup-minded ecosystem backed by the fortress balance sheet of J.P. Morgan, Chase UK designs cloud-native products focused heavily on customer centricity. The division cultivates a flat-structure engineering culture that values deep curiosity, inter-squad collaboration, and modern application development methodologies to build the bank of the future.

About the Role: Data Scientist Lead – Fraud Strategy & Analytics

Are you an expert analytical thinker who thrives at the intersection of predictive science, behavioural analysis, and proactive system defence? The Chase UK Fraud Strategy & Analytics division is accepting applications for a Data Scientist Lead at its iconic Canary Wharf corporate headquarters in London.

In this high-impact lead role, you will protect millions of retail banking customers by designing, developing, and deploying data-driven fraud mitigation strategies. Operating within an agile, flat-structured architecture, you will lead end-to-end projects across all stages of the software development lifecycle (SDLC). This position isn’t restricted to isolated modelling silos; you will have the autonomy to move fluidly between collaborative squads, engineering microservices applications, translating fraud rules into live operational impacts, and partnering with risk management teams to shut down malicious actors in real time.

Key Responsibilities & Predictive Engineering Workflows

• Develop Fraud Mitigation Architectures: Build, refine, and deploy advanced data models, decision trees, and rule-based strategies to catch and block evolving fraudulent patterns.

• Lead Fraud Strategy Analytics: Run deep exploratory data analysis on transaction streams to identify anomalies, optimise operational workflows, and enhance financial crime defences.

• Operational Integration: Translate complex data science concepts and fraud behaviours into concrete operational procedures that boost automated decision accuracy and system efficiency.

• Collaborate with Risk & Safety Squads: Work hand-in-hand with specialised fraud risk teams to audit, test, and validate the long-term effectiveness of active models and rulesets.

• Data-Driven Compliance & Controls: Build data confirmation frameworks to ensure all deployed models strictly align with internal risk limits, corporate audit criteria, and external banking regulations.

• Knowledge & Team Mentorship: Lead by example within flat structures, managing and scaling internal talent while sharing analytical best practices across the broader global JPMorganChase engineering community.

Candidate Prerequisites & Technical Capabilities

This role requires a unique combination of high-level quantitative expertise, financial product intuition, and the leadership capacity needed to guide technical squads.

Required Technical & Professional Expertise:

• Academic Foundation: A Master’s degree in a highly quantitative or STEM discipline (such as Statistics, Computer Science, Data Science, Mathematics, or an equivalent field).

• Domain Expertise: Clear, functional understanding of core fraud mechanisms, financial crime patterns, and banking products.

• Leadership & Management: Demonstrated experience leading, mentoring, or developing technical talent within an engineering or data analysis environment.

• Communication Skills: Superior written, oral, and presentation capabilities, with a proven ability to distill complex analytical findings into brief, high-level summaries for executive teams.

Preferred Technical Assets (Bonus Points):

• Hands-on experience navigating or contributing to cloud-native microservices applications.

• Familiarity working within highly agile, fast-paced fintech environments or digital banking platforms.

• Strong commercial awareness with a highly practical, solution-oriented approach to complex risk challenges.

• Ability to thrive in multi-disciplinary squads and adapt quickly to shifting project scopes.

Key Job Details

• Job Identification: 210730776

• Job Category: Predictive Science

• Primary Location: 1 Cabot Square, London, E14 4QJ, United Kingdom

• Schedule & Classification: Full-Time corporate sector schedule