Use your analytics knowledge, collaboration skills, and team leadership in an exciting role.

As an Analytics Manager on the Payment Analytics Team, you’ll work closely with Product Owners to deliver insights in terms of descriptive, diagnostic, predictive, and prescriptive analytics. You’ll build solutions around data mining, reporting, data management, and data transformation that support management of payment platforms. Your work on a cross-functional team to deliver analytics and reporting to stakeholders.  Your responsibilities will focus on writing complex queries and creating utilities and applications heavily focused on large DB2, SQL, and AWS database platforms across multiple LOBs.

Job Responsibilities

Lead a team of analysts that supports Payments Product Owners Champion data and analytics best practices across the Payments organization Understand and translate business needs into data models supporting long-term solutions Facilitate the creation of data models using best practices to ensure high data quality and reduced redundancy Partner with across the organization to understand business requirements and objectives Create solutions to combine data from multiple sources for analysis and reporting Collaborate with analytic and non-analytic groups as well as facilitate holistic, cross-functional learning

Required qualifications, capabilities, and skills

Bachelor’s degree and 5+ years of experience in related and applicable data analytics functions Previous experience managing analysts Intermediate knowledge of SQL, Alteryx, SAS, and Python Experience with Hadoop, Teradata, Oracle, and Cloud databases Adept at explaining and converting complex concepts into digestible information to be consumed by audiences of varying levels of expertise Degree in quantitative or related field preferred Functional industry knowledge for banking and payments

Preferred qualifications, capabilities, and skills

MS Degree in a related discipline Functional industry experience in operations, marketing, credit/risk, technology or finance Intermediate knowledge of Machine Learning

Hybrid-60% in-office

Please note: Relocation assistance is not offered/supported for this role