Backend Engineer

• Analyze data related to fraud resulting from identity verification and validation challenges
• Support existing teams in solving enterprise-level problems
• Architect and engineer Machine Learning/AI solutions for anomaly detection and entity behavior evaluation
• Improve data quality through advanced data modeling
• Implement Extract, Transform, Load (ETL) technologies
• Work with highly structured data
• Utilize data platforms and analytics tools such as Databricks and Zingg
• Develop data visualization packages
• Communicate and collaborate with multiple functional groups

Data Scientist – Identity Analytics, Fraud Detection, Python, Spark, Databricks

Backend Software Engineer III

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