Digital Payments Fraud Strategy Analyst

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.
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

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