Digital Payments Fraud Strategy Analyst

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Regular or Temporary:

Regular

Language Fluency:  English (Required)

Work Shift:

1st shift (United States of America)

Please review the following job description:

Perform digital payment fraud analyses and strategy support using analytics tools to provide actionable insights and real-time changes to fraud detection tools. A key part of the role will be regularly providing guiding consultation to business leaders and other stakeholders on best methods of leveraging analytics and fraud strategies to reduce fraud risk while maintaining a world class customer experience for our clients. This job will support real-time fraud detection rule systems where the role will be actively involved with developing, and demonstrating a mastery of digital payments, fraud, and advanced analytics while working in a team environment.

ESSENTIAL DUTIES AND RESPONSIBILITIES
Following is a summary of the essential functions for this job.  Other duties may be performed, both major and minor, which are not mentioned below.  Specific activities may change from time to time.  

ESSENTIAL DUTIES AND RESPONSIBILITIES
1.    Independently perform sophisticated fraud detection monitoring of fraud patterns using advanced analytics and dashboard tools such as SAS, Python, Tableau, Excel pivot, etc.
2.    Develop new queries, and data insights through use of SQL query statements leveraging the Truist data lake environments that involve querying big data necessary to support analyses in the lower analytical environments
3.    Build analytical tools that provide faster visibility to emerging workforce management imbalances by quadrants of risk for alerts generated by fraud rules that are distributed to queues worked by fraud operations partners both onshore and offshore ( High / Medium / Low )
4.    Utilize benchmarking tools to understand opportunities to further improve fraud performance with respect to approval rates, and gross / net fraud basis points
5.    Develop weekly time series and compelling data visualizations to organize fraud run rates for both eligible and ineligible fraud trends being observed with analytical tools designed to rapidly identify emerging / new fraud patterns while presenting the outcomes to a wide array of stakeholders
6.    From new fraud patterns identified, demonstrate capability to take fast actions to stop new fraud trends as they emerge using rule platforms and alerting capabilities through demonstrating value of identifying a fraud forecast and false positive rate of the pattern identified
7.    Build out advanced segmentation capabilities for assigned digital payment products and methods of product use to support reduction of false declines and where current fraud rules contribute to elevated false positive rates
8.    Demonstrate capability in assigned fraud strategy and analytics projects to build process / project documentation so that rules, reports, techniques are adequately documented in a way that others can follow and learn from new analytics tools and routines
9.    Build/Support complex data wrangling tools that determine the differences between digital payment transactions, authentications, and clearing records while understanding how these items relate to fraud claims and/or types of fraud case alerts generated by fraud rule systems for assigned rule platforms

QUALIFICATIONS
Required Qualifications:
The requirements listed below are representative of the knowledge, skill and/or ability required.  Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions.
1.    Bachelor’s degree and zero to four or more years of experience in a quantitative field such as Finance, Mathematics, Analytics, Data Science, Computer Science, or Engineering, or equivalent education and related training 
2.    Exhibit understanding of statistical methods, including a broad understanding of classical statistics, probability theory, econometrics, time-series, and primary statistical tests
3.    Familiarity with linear algebra concepts for optimization, complex matrix operations, eigenvalue decompositions, and principal components; working knowledge of calculus/differential equations, with understanding of stochastic processes
4.    Demonstrate understanding of data cleansing and preparation methodologies, including regex, filtering, indexing, interpolation, and outlier treatment
5.    Strong familiarity with data extraction in a variety of environments (SQL, JQuery, etc.)
6.    Working knowledge of Hadoop, Pig, Hive, and/or NoSQL, Spark
7.    Experience in managing multiple projects with tight deadlines in a collaborative environment

Preferred Qualifications:
1.    Master’s degree or PhD in a quantitative field such as Finance, Mathematics, Analytics, Data Science, Computer Science, or Engineering
2.    Four years of relevant work experience if candidate lacks graduate degree
3.    Previous experience in the banking or fin-tech industry

Truist supports a diverse workforce and is an Equal Opportunity Employer who does not discriminate against individuals on the basis of race, gender, color, religion, national origin, age, sexual orientation, gender identity, disability, veteran status or other classification protected by law. Drug Free Workplace.

Thank you for your interest in Truist! BB&T and SunTrust have come together in a transformational merger of equals to create Truist, the premier financial organization in the country. You may notice references to our legacy company names, BB&T and SunTrust, in places throughout this site. All such references should be understood to refer to Truist moving forward while we continue to transition to the Truist name.