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Known brand, metro location, mid-level generalist data role and broad required skills increase competition.
Fraud and integrity domain knowledge is emphasized, reducing cross-industry transferability despite analytic skills.
Explicit 4+ years requirement plus mandatory SQL, Python, and Spark skills enforce strict shortlisting.
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Own end-to-end complex risk analytical problems across 1 to 3 Problem Space Teams, focusing on platform integrity and real-time risk protection.
Leverage advanced AI and analytic systems to detect new fraud, safety, and identity abuse typologies and develop real-time protective measures.
Build data inputs, perform feature engineering, use synthetic data simulations, communicate with senior stakeholders, and mentor junior analysts to improve risk mitigation.
4+ years of experience in data-related or quantitative fields.
Bachelor's Degree in Analytics, Statistics, Computer Science, or Engineering.
Strong proficiency in SQL, Python, Spark, and statistical/experimentation techniques.
Proficient understanding of AI/ML, Feature Engineering, and System-Thinking.
Experienced with independent execution on complex analytical problems within risk or integrity domains involving fraud, safety, or identity.
Comfortable working with AI-driven analytics, agentic setups, and system-level feature engineering.
Skilled at stakeholder communication and mentoring juniors in analytics teams focused on operational improvements and automation.