Minimum of 10 years related work experience in fraud strategy or fraud data science field.
Understanding of statistical methods, including classical statistics, probability theory, econometrics, and time-series analysis.
Strong familiarity with data extraction in environments like SQL. Working knowledge of Python, Hive, Spark, AWS Sagemaker.
Undergraduate degree or equivalent combination of training and experience. Graduate degree preferred.
Lead development of fraud strategies in fraud prevention systems
Independently perform sophisticated data analytics using structured and unstructured data
Leverages deep analytics and statistics knowledge to determine risk, and develop plans for success
Collects, analyzes, and communicates statistics related to daily fraud mitigation operations to stakeholders
Leads and analyzes processes, products and reviews the validation of scalable analyses
Develops a technology strategy and manages vendor relationships supporting the delivery of analytical capabilities
