You will be responsible for the delivery of business-critical data and analytics deliveries relating to themes such as fraud detection/mitigation, trending, false positive reduction, analytics and rule development.
Job Responsibilities
- Support 3-5 year horizon plans for Payments fraud strategy across all major core-cash products and stakeholder groups
- Work with a Machine Learning / Artificial Intelligence (ML/AI) data science team on analytical models to identify patterns in data, spot data anomalies & predict fraud trends, all of which facilitate fraud prevention, detection and recover.
- Manage a central Core-Cash Fraud Strategy team and aligned to the business goals/objectives to support JPM Payments.
- Drive very defined business objectives across KPI and KRI under Core-Cash Fraud Strategy which align to detection, prevention and facilitate data for recovery.
- Support Monthly Business Reviews (MBRs) to showcase the value-add of analytics, trending / ML/AI and data for the JPM Payments franchise, including the delivery of a cohesive communication strategy on data modernization to all major stakeholder groups (including Product, Relationship, Legal, Compliance, Cyber, Technology and cross-LOB data organizations)
- Act as a primary global escalation point for Fraud Detection related inquiries
- Support Ad-hoc research and resolution of daily issues, data requests, reporting requirements, as well as any regulatory requests that impact fraud data and analytics delivery.
- Drive the implementation and tracking of JPM Payments core-cash fraud detection rules and performance of such rules including data modernization and ML/AI initiatives.
- Work with the global product organization and wider stakeholder teams to create a consistent analytics, ML/AI and data execution model from a requirement prioritization and governance standpoint (where applicable)
- Articulate complex ideas and analytical communications in a succinct way, including being comfortable recording demos and presenting to large audiences and very senior executives.
Required Qualifications, Capabilities and Skills
- Minimum of 7 years' in financial services (e.g. in Payments, Treasury, Fintech, or any Corporate/Investment Banking function) with a data/analytics background
- Minimum of 2 years' experience leading a team and developing talent, managing projects and using project management tools (e.g., JIRA, confluence, Microsoft Teams)
- Must have a background in Fraud Prevention, Data Science, Analytics, Product Development & Technology
- Must have experience with working with technology and/or data scientists to build analytics ML/AI products is a requirement
- Must have excellent written and oral communication and presentation skills, with experience communicating effectively with diverse audiences – across business and technology partners, including senior leadership with high aptitude for influencing business decisions
- Must have the ability to influence and effectively lead cross-functional teams in a fast-paced environment where there are multiple, urgent priorities with short deadlines
- Self-starter with out-of-the box problem-solving skills, able to bring new ideas to life, particularly where business requirements are unclear/incomplete
- Must display keen attention to detail, strong organization skills, effective time management and thorough follow-up when bottlenecks prevent certain programs/controls from being delivered
Preferred Qualifications, Capabilities, and Skills
- Comprehensive IT knowledge - full suite of Microsoft Office products and ideally Alteryx / Python and/or Tableau knowledge to support data mining and data modelling
- The undergraduate degree should have some components relating to a quantitative field (e.g. Computer Science, Data Analytics, Economics, Statistics modules, Finance etc.)
- Basic knowledge of ML/AI modelling techniques that can be leveraged within the banking sector (e.g. supervised and unsupervised Machine Learning models)