Do you have a strategic mind set to lead initiatives and improve processes within Consumer & Community Banking (CCB) operations? If so, this is the role for you. 

As a Quantitative Analytics Associate  in the Point of Sale Central Analytics Team in Fraud Customer Protection Services, you will join a forward-thinking team that seeks to prevent plastics fraud through data-driven analysis. You will develop and advance reporting dashboards, optimize data consumption practices, and work with cross-business partners to promote benefits in all aspects of fraud prevention. Your role will involve analyzing big data, understanding complex systems, identifying opportunities, and creating solutions. We are looking for a self-driven problem solver with a strong sense of ownership

Job responsibilities: 

Gain a thorough understanding of the full lifecycle of a point-of-sale transaction to deliver timely, efficient, and fit-for-purpose solutions.Analyze large datasets to identify patterns, trends, and anomalies that may indicate fraudulent activity.Build, develop, and maintain reporting systems, data automation systems, and dashboards to communicate findings and insights to leadership for strategic decision-making.Support the modernization of reporting infrastructure on the cloud by performing ad hoc analyses to ensure data integrity and communicating progress to senior management.Continuously seek to enhance internal analytical techniques and introduce best practices to improve key business metrics.Work both independently and collaboratively with cross-functional partners to complete analytical tasks, beginning with problem identification, analyzing large and complex data, and formulating concise conclusions with actionable recommendations

Required qualifications, capabilities, and skills: 

MS degree with 3 years of experience in Risk Management or another quantitative field, orBS degree with a minimum of 5 years of experience in Risk Management or another quantitative field.Strong background in statistics, mathematics, or a related quantitative field.Hands-on experience with SAS, SQL, and Alteryx.Advanced knowledge of Tableau or equivalent data visualization platforms.Ability to query large datasets and transform raw data into actionable insights.Strong communication and interpersonal skills, with the ability to interact effectively with individuals across departments/functions, including senior-level executives.

Preferred qualifications, capabilities, and skills:

Python programming skillsFamiliarity with data mining and other advanced analytics techniquesSelf-starter with ability to push for resolution

 

Schedule: Monday thru Friday 8:00am to 5:00pm