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

Job Responsibilities:

You will be responsible for supporting Commerce Enablement Trust and Security team to:

• 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

Required qualifications, capabilities, and skills:

• 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

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