Fraud and Risk data analyst II : 25-04912 Fraud and Risk data analyst II : 25-04912 Get AI-powered advice on this job and more exclusive features. Primary Skills: SQL (Expert), Databricks (Advanced), Python (Advanced), Quicksight (Advanced), Risk/Fraud Analytics (Expert), Contract Type: W2 Contract Duration: 12+ Months Location: Mountain View CA (Hybrid, 3 days onsite)(LI-HYBRID) Pay Range: $65.00 - $71.00 Per Hour #LP Job Summary We are seeking a Senior Data Analyst for our Risk Operations team, who will coordinate closely with risk analytics, data capabilities teams, and executives to translate business requirements into actionable technical plans. The ideal candidate will constantly seek improvements and automation of manual processes utilizing data, machine learning, and analytics. The role involves optimizing scripts, models, and leveraging data to deeply understand our products, identify risk trends, and influence relevant teams. Key Responsibilities Translate business requirements into clear technical action plans and execute on these plans while communicating progress and mitigating roadblocks. Utilize data, machine learning, and analytics to automate manual processes and improve existing systems. Leverage data analytics to understand product intricacies and identify trends indicating elevated risk, influencing related teams accordingly. Optimize the performance of scripts, reports, and models for accurate risk operations metrics tracking and reporting. Collaborate with engineers to develop, test, debug, and maintain server-side data collection and other database sources for reliable operations metrics. Must-Have Skills Expert proficiency in SQL and advanced skills in analytical tools and programming languages such as Python. Strong ability to build effective data visualizations and proficiency in using tools like Quicksight and Databricks. Exceptional communication skills with the capability to present findings to both technical and non-technical audiences. Industry Experience Required 3-5 years experience in data analytics/data science/operations research, preferably within Financial Services or FinTech sectors.
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