Quant Analytics Manager Vice President - Trust and Security

JPMorgan Chase & Co.•Plano, TX

22d

About The Position

We are seeking a Vice President Quant Analytics Manager who will be a key member of Connected Commerce, Commerce Enablement Analytics team supporting Trust and Security Data work stream within 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

Requirements

8+ 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 determination and demonstrated ability to deliver against multiple timelines, goals, stakeholder needs and expectations across internal partners and senior management

Nice To Haves

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

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
Apply creative and strategic thought to craft and deliver compelling and impactful insights to influence stakeholders through data visualization techniques and effective storytelling
Collaborate with executive leadership to articulate vision, goals and roadmap for data driven decision-making across the organization
Drive 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 drive 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