Be at the heart of actionFly remote-controlled drones into enemy territory to gather vital information.

Apply Now

Lead Data Scientist - Fraud

JPMorgan Chase & Co.
City of London
2 weeks ago
Create job alert
Overview

We know that people want great value combined with an excellent experience from a bank they can trust, so we launched our digital bank, Chase UK, to revolutionise mobile banking with seamless journeys that our customers love. We're already trusted by millions in the US and we're quickly catching up in the UK - but how we do things here is a little different. We're building the bank of the future from scratch, channelling our start-up mentality every step of the way - meaning you'll have the opportunity to make a real impact.

As a fraud data scientist at JPMorgan Chase within the International Consumer Bank, you will be a part of a flat-structure organization. Your responsibilities are to deliver end-to-end cutting-edge solutions in the form of cloud-native microservices architecture applications leveraging the latest technologies and the best industry practices. You are expected to be involved in the design and architecture of the solutions while also focusing on the entire SDLC lifecycle stages.

Our fraud analytics team is at the heart of this venture, focused on getting smart ideas into the hands of our customers. We\'re looking for people who have a curious mindset, thrive in collaborative squads, and are passionate about new technology. By their nature, our people are also solution-oriented, commercially savvy and have a head for fintech. We work in tribes and squads that focus on specific products and projects - and depending on your strengths and interests, you\'ll have the opportunity to move between them.

Job spec requirements

The Fraud & Financial crime Product function leads the 1st line of defense business for fraud & financial crime risk, including ownership of the fraud & financial crime strategy and control framework across all products and channels. Working inside a specialist fraud team to ensure transaction monitoring and controls are optimized to reduce fraud & financial crime risk whilst ensuring 1st class client experience - you will be supporting the product from an Analytics perspective.

Job responsibilities
  • Responsible for development and implementation of fraud strategies/rules to effectively detect fraudulent activities
  • Conduct analytics to support fraud product, fraud operations and fin crime to protect the financial interest of the customers and the bank
  • Conduct analytics to support fraud operation team to improve efficiency and decision accuracy, including translation of fraud strategy into fraud operation impact
  • Working with the 2nd line fraud risk teams to ensure models, rulesets and strategies are effective.
  • Ensuring all compliance, audit & control frameworks are followed - using data to support the confirmation of these processes are adhered to regulation standard.
  • Sharing best practice across JP Morgan Chase & Co.
  • Superior written, oral communication and presentation skills with experience communicating concisely and effectively with all levels of management and partners
Required qualifications, capabilities and skills
  • Master\'s degree in numeric fields or STEM related fields, such as statistics, computer science, data science, etc
  • Knowledge of Fraud / Financial crime processes and products
  • Team development and management experience required.
About Us

J.P. Morgan is a global leader in financial services, providing strategic advice and products to the world\'s most prominent corporations, governments, wealthy individuals and institutional investors. Our first-class business in a first-class way approach to serving clients drives everything we do. We strive to build trusted, long-term partnerships to help our clients achieve their business objectives.

We recognize that our people are our strength and the diverse talents they bring to our global workforce are directly linked to our success. We are an equal opportunity employer and place a high value on diversity and inclusion at our company. We do not discriminate on the basis of any protected attribute, including race, religion, color, national origin, gender, sexual orientation, gender identity, gender expression, age, marital or veteran status, pregnancy or disability, or any other basis protected under applicable law. We also make reasonable accommodations for applicants\' and employees\' religious practices and beliefs, as well as mental health or physical disability needs. Visit our FAQs for more information about requesting an accommodation.

About the Team

Our professionals in our Corporate Functions cover a diverse range of areas from finance and risk to human resources and marketing. Our corporate teams are an essential part of our company, ensuring that we\'re setting our businesses, clients, customers and employees up for success.


#J-18808-Ljbffr

Related Jobs

View all jobs

Lead Data Scientist

Lead Data Scientist

Lead Data Scientist

Lead Data Scientist

Lead Data Scientist

Lead Data Scientist

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Data Science Recruitment Trends 2025 (UK): What Job Seekers Need To Know About Today’s Hiring Process

Summary: UK data science hiring has shifted from title‑led CV screens to capability‑driven assessments that emphasise rigorous problem framing, high‑quality analytics & modelling, experiment/causality, production awareness (MLOps), governance/ethics, and measurable product or commercial impact. This guide explains what’s changed, what to expect in interviews & how to prepare—especially for product/data scientists, applied ML scientists, decision scientists, econometricians, growth/marketing analysts, and ML‑adjacent data scientists supporting LLM/AI products. Who this is for: Product/decision/data scientists, applied ML scientists, econometrics & causal inference specialists, experimentation leads, analytics engineers crossing into DS, ML generalists with strong statistics, and data scientists collaborating with platform/MLOps teams in the UK.

Why Data Science Careers in the UK Are Becoming More Multidisciplinary

Data science once meant advanced statistics, machine learning models and coding in Python or R. In the UK today, it has become one of the most in-demand professions across sectors — from healthcare to finance, retail to government. But as the field matures, employers now expect more than technical modelling skills. Modern data science is multidisciplinary. It requires not just coding and algorithms, but also legal knowledge, ethical reasoning, psychological insight, linguistic clarity and human-centred design. Data scientists are expected to interpret, communicate and apply data responsibly, with awareness of law, human behaviour and accessibility. In this article, we’ll explore why data science careers in the UK are becoming more multidisciplinary, how these five disciplines intersect with data science, and what job-seekers & employers need to know to succeed in this transformed field.

Data Science Team Structures Explained: Who Does What in a Modern Data Science Department

Data science is one of the most in-demand, dynamic, and multidisciplinary areas in the UK tech and business landscape. Organisations from finance, retail, health, government, and beyond are using data to drive decisions, automate processes, personalise services, predict trends, detect fraud, and more. To do that well, companies don’t just need good data scientists; they need teams with clearly defined roles, responsibilities, workflows, collaboration, and governance. If you're aiming for a role in data science or recruiting for one, understanding the structure of a data science department—and who does what—can make all the difference. This article breaks down the key roles, how they interact across the lifecycle of a data science project, what skills and qualifications are typical in the UK, expected salary ranges, challenges, trends, and how to build or grow an effective team.