Company : Verisk
Country: United States
Location : Jersey City, New Jersey
Post: Sat, 01 Oct 2022 04:23:15 GMT
Expires: Sat, 29 Oct 2022 23:59:59 GMT
Apply Job : Apply Online
—————————— Job Description ——————————
The Fraud Data Scientist is an essential member of a team that helps lead and implement analytical strategies and solutions to detect fraud and support other analytic initiatives within Verisk’s Anti-Fraud Solutions Group (AFSG). This role helps plan and execute holistic strategies to develop anti-fraud solutions that are both highly accurate and meaningful at addressing the most critical fraud detection and investigation needs of the US insurance market. The position works alongside industry subject matter experts in AFSG and development resources across the organization to implement product vision, bringing creative and powerful anti-fraud solutions to market. They work closely with clients across a variety of engagements, from Proof of Concepts (POCs) to supporting existing client needs.
Responsibilities & Essential Duties:
· Implement analytical techniques to detect and prioritize fraud propensity risk including but not limited to business rules, anomaly detection, predictive modeling, and network analytics.
· Lead entity resolution problem solving and continual improvement efforts to optimize both data prep and entity resolution algorithm configurations.
· Support end to end data pipeline including acquisition, cleansing, validation, feature engineering, scoring, and alert generation.
· Work closely with subject matter experts and other technical project team members to define analytical strategy based on customer needs.
· Provide solution recommendations and/or ideas to product owners and stakeholders to increase value of solution.
· Work closely with internal project team and client teams to help deliver POC’s and support other client needs as required.
· Take on the analytic lead role over end to end solution delivery to help steer development progress to meet project milestones on time.
· Assist in monitoring for data quality issues, reporting data quality concerns, and helping remediate data issues promptly with support from data engineering and other technical teams as required.
· Report status of work and analytical findings to project team and stakeholders.
· Explore new data sources and analytic insights to embed in solution outputs.
· Complete all responsibilities as outlined on annual Performance Plan.
· Complete all special projects and other duties as assigned.
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