Dedicated to analyzing data related to fraud arising from identity verification and validation challenges.
Conduct detailed analysis, evaluations, and provides recommendations for improvements, optimization, development, and maintenance efforts addressing client-specific or mission-critical issues.
Consults with clients to define business needs, challenges, and objectives.
Oversee analytical studies, leads surveys, and performs data collection to support data-driven recommendations and solution development.
Requirements
A degree from an accredited College/University in the applicable field of services is required.
If the individual's degree is not in the applicable field, then 4 additional years of related experience
8+ years of overall IT-related experience
3+ years of experience as a data engineer / data analyst
3+ years architecting and engineering Machine Learning/AI based solutions to large scale enterprise problems solving anomaly detection, entity behavior evaluation and prediction, and data quality improvement
Experience with data platforms and analytics tools (specifically Databricks and Zingg)
Experience with NoSQL, R, or Python and Spark
Experience with advanced data modeling and how to make that data usable for meeting mission requirements (including entity resolution)