Data Scientist, Fraud Strategic Analytics
JPMorganChase
Job Overview
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Job Description
Data Scientist, Fraud Strategic Analytics at JPMorganChase
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 Data Scientist, Fraud Strategic Analytics 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 Strategy and analytics functions leads the 1st line of defense business for fraud risk, including ownership of the fraud 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 processes and products
- Team development and management experience required.
Key skills/competency
- Fraud Detection
- Strategic Analytics
- Cloud-Native Architecture
- Microservices
- Data Science
- Machine Learning
- Risk Management
- Compliance Frameworks
- SQL
- Financial Crime
How to Get Hired at JPMorganChase
- Research JPMorganChase's culture: Study their mission, values, recent news, and employee testimonials on LinkedIn and Glassdoor to align with their innovative spirit.
- Customize your Data Scientist, Fraud Strategic Analytics resume: Tailor your application to highlight experience in fraud detection, strategic analytics, and cloud technologies, using keywords from the job description.
- Showcase analytical and technical skills: Prepare to discuss your proficiency in data science tools, machine learning for fraud, and experience with microservices architecture.
- Prepare for behavioral interviews: Practice articulating your problem-solving approach, collaboration style, and commercial acumen, especially within a fintech context.
- Demonstrate commitment to compliance: Be ready to discuss your understanding of regulatory frameworks and data governance in financial services.
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