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Fraud Strategy & Detection Lead

Business Management & Operations
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TIAA is a unique financial partner. With an award-winning track record for consistent performance, TIAA is the leading provider of financial services in the academic, research, medical, cultural and government fields. TIAA has $1 trillion in assets under management (as of 9/30/2018) and offers a wide range of financial solutions, including investing, banking, advice and guidance, and retirement services.


For more information about TIAA, visit our website.




The Lead Data Analyst will be responsible for fraud detection and prevention strategy and analytics in the Enterprise Financial Crimes Prevention group.  This individual will develop sound risk identification and fraud detection and prevention strategy utilizing available fraud data while balancing risk and reward including operational efficiency and customer experience.  They will work with leading vendor and proprietary authentication and counter-fraud technologies.  He or she will be expected to possess or rapidly develop expertise of TIAA products and businesses as well as internal processes and counter-fraud skills. They will partner with the program management, product management, fulfillment, analytics; risk, operations, data and technology teams to ensure changes are fully developed, prioritized, tested and executed in a timely manner.



The Lead Data Analyst will provide creative thought leadership and apply strong technology, data, analytics and counter-fraud knowledge and experience to develop protection strategies for multiple channels and products around customer authentication, loss prevention, and fraud detection.   They will perform data mining, analytic problem solving and detailed risk and operations assessments to deliver succinct and actionable findings for implementation and communicate to multiple teams and committees across the organization. Responsibilities will include recurring and ad-hoc data analysis and programing using SAS, R, and SQL.


Required Qualifications:

  • Minimum of 5 years in financial services industry with direct experience in development of data driven strategies
  • Bachelor’s Degree in Business, Finance, Technology, Applied Math, Statistics or related field

Preferred Qualifications:

  • Master’s Degree
  • Strong Fraud prevention and detection experience
  • Solid data extraction, transformation and analysis skills along with ability to develop business case for change while anticipating questions / objections       
  • Experience with technologies  like SAS, R, Oracle, SQL, Hadoop, Splunk, Tableau, Actimize, Threatmetrix
  • AI, machine learning, data modeling experience
  • Cyber-fraud experience
  • Demonstrate initiative with ability to work independently or as a member of a team
  • Ability to manage multiple, concurrent projects and tasks
  • Excellent oral and written communication skills
  • Work well under pressure
  • Attention to detail
Equal Employment Opportunity is not just the law, it’s our commitment. Read more about the Equal Employment Opportunity Law.

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We are an Equal Opportunity/Affirmative Action Employer. We will consider all qualified applicants for employment regardless of age, race, color, national origin, sex, religion, veteran status, disability, sexual orientation, gender identity, or any other legally protected status.

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