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Tier-1 bank, mid-level analytics role in metro with generalist Python/SQL skills increases candidate competition.
Analytics skills transfer, but fraud and banking controls require domain experience, so sensitivity is moderate.
Degree plus explicit years and required Python/SQL/Looker skills enforce strict screening.
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Design, validate, and manage fraud strategies balancing fraud mitigation, financial performance, customer experience, and operational efficiency.
Develop data pipelines and Looker dashboards to monitor fraud trends, losses, and customer friction points.
Partner with Product, Technology, and Operations to design, test, and implement fraud detection and treatment solutions while ensuring compliance and control frameworks.
MS degree with 3+ years or BS degree with 4+ years experience in risk management or data analytics.
Proficiency in Python, SQL, Github, Looker, and Excel is required.
Strong analytical skills with knowledge in AI and machine learning for fraud detection is mandatory.
Work Experience Required: 3+ years with MS degree, 4+ years with BS degree in relevant fields.
Experienced in fraud risk management or analytics, preferably with specific fraud domain exposure.
Capable of strategic thinking with ability to develop roadmaps and drive execution balancing short- and long-term solutions.
Strong collaborator able to work cross-functionally with product, technology, operations, and risk teams in a regulated environment.