Quant Analytics Senior Associate - Trust & Security

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