Fraud Risk Analyst

Fiserv•Columbus, OH
•$74,000 - $122,400

About The Position

The Fraud Risk Analyst executes analytical processes to detect fraud attacks, analyze their impacts, determine effective prevention and mitigation strategies, and monitor the performance of the fraud risk ecosystem. The role evaluates root causes, observed volumes, and financial and operational impacts, and recommends remediation paths. It creates fact- and data-based insights to inform and influence organizational change.

Requirements

  • Bachelor’s degree in Business and/or Computer Science, or equivalent work experience.
  • 3+ years of related work experience in FinTech, e-commerce, banking, and/or fraud prevention.
  • 3+ years of experience as a Data Analyst.
  • Competency in Python, PySpark, SQL, and/or comparable data analysis skills using Snowflake, Palantir, AWS, Azure, Splunk, Power BI, Actimize, or other fraud prevention platforms for building fraud prevention rules and artificial intelligence/machine learning models.
  • Experience mining complex datasets and generating business reports.
  • Experience developing, creating, and presenting complex concepts and outcomes to senior leaders in support of positive ROI and fraud reduction.
  • Valid and unrestricted U.S. work authorization; candidates requiring sponsorship now or in the future are not eligible.

Nice To Haves

  • Master’s degree in Computer Science or a related field.
  • Fraud certification such as ACAMS CAFS or ACFE.
  • Coding certification and/or documented supporting use case or education.

Responsibilities

  • Enhance and execute analysis to identify new fraud attacks, detect attack signatures, and determine the root cause of fraud events observed or attempted in the network using financial and non-financial cardholder account data.
  • Maintain and monitor early-warning monitors to identify abnormal activity and possible precursor attack activity, producing dashboards, daily monitoring reports, and ad hoc reports.
  • Source and analyze information to determine root causes and effective mitigation options across the network.
  • Manage fraud ecosystem measures to monitor the effectiveness and performance of fraud controls.
  • Conduct ad hoc analysis and maintain analytical capabilities and datasets to support accuracy and speed.
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