Join a team where your analytical expertise directly protects customers and drives meaningful impact across one of the world's leading financial institutions. As part of JPMorganChase's Connected Commerce organization, you'll be at the intersection of data strategy, fraud prevention, and customer trust — working alongside talented technologists, product leaders, and analytics professionals who are passionate about solving complex problems at scale. This is an opportunity to grow your career while contributing to work that matters, in an environment that values curiosity, collaboration, and continuous learning.

As a Quant Analytics Sr. Associate within Connected Commerce, Commerce Enablement Analytics team supporting Trust and Security Data work stream, you will be a key member of the broader Data and Analytics organization.  You will work closely with Product Owners, Data Owners, Tech and Data & Analytics across Consumer and Community Banking to deliver data strategy and analytics initiatives supporting Trust and Security 

Job Responsibilities:

• Deliver analytical approaches to identify opportunities to improve fraud and scam prevention efforts focused on protecting our customers while balancing customer satisfaction  
• Develop and maintain comprehensive data strategy roadmap collaborating with Data Owners, Tech, Product owners aligned with Business goals and regulatory requirements  
• Collaborate with stakeholders to understand business priorities and translate them to actionable data initiatives  
• Collaborate with executive leadership to articulate vision, goals and roadmap for data promoten decision-making across the organization  
• Promote the adoption of best practices in data management and analytics within the organization within the organization through training, mentoring and knowledge sharing  
• Continuously monitor and optimize data processes, analytical models, and infrastructure to promote continuous improvement and innovation  
• Bring order to disparate requirements with high tolerance for ambiguity, very strong problem solving ability, and excellent client engagement skills  
• Pivot quickly as client guidance evolves, always keeping the ultimate project objective in mind. Manage evolving project requirements while continuously learning quickly on-the-job  
• Establish and embrace guidelines to ensure consistency and high quality of presentation materials in appearance, tone, and style  

• Collaborate with unit managers, end users, developers, and other stakeholders to integrate data discoveries and processes into operational capabilities

   

Required qualifications, capabilities, and skills:

• 4+ years of industry experience in Data & Analytics
• Bachelor’s degree in relevant quantitative field required (e.g. Analytics, Statistics, Economics, Applied Math, Operations Research, Physics, Data Science fields); 
• Must have prior experience working in Digital and/or product analytics and in depth understanding of common digital metrics and definitions
• In general, top-tier talent, as demonstrated by performance history and educational background/accomplishments
• Ability to work in large and medium sized project teams, as self-directed contributor with a proven track record of being detail orientated, innovative, creative, and strategic, with ability to influence and effectively collaborate with cross-functional teams
• Demonstrated ability to define business KPIs and establish measurement frameworks
• Structured thinker with passion for analyzing results and digging deeper and a strong aptitude for technical concepts and ideas
• Experience across broad range of modern analytics tools (e.g., SQL, AWS, Hive, Hadoop, Spark, Python, R) and working on Digital behavioral data tools (E.g.: Adobe Analytics)
• Superior written and oral communication and presentation skills with experience communicating effectively with diverse audiences – across business and technology partners, including senior leadership
• Self-starter with out-of-the box problem solving skills and a drive to bring new ideas to life
• Strong time-management skills, with the ability to multi-task and keep numerous projects on track

Preferred qualifications, capabilities, and skills:

• Basic knowledge in modern data mining, quantitative research, and data science techniques (e.g., decision trees, regressions, machine learning, string similarity, behavioral analytics, look-a-like models) 
• Financial services background 
• Advanced degree in relevant quantitative field