Responsible for complex model and attribute validation from development through post-implementation and monitoring across Insurance Data Services.
Report out progress and final results to necessary audiences with little guidance. Subject matter expert in several areas of Predictive Analytics and respective data sources like Credit Bureau, Public Records and additional data sources integrating into our systems. Able to lead and contribute to automation efforts and process improvement. Proficient in using/understanding multiple programming languages at the intermediate level. Familiarity with cloud computing.
1. Key Contributor to the advancement of the group’s technical and analytical knowledge-base; organize and present at training sessions between other departments.
2. Self-sufficient with projects - being able to develop test plans, efficiently validate results, work with other teams to solve problems, and represent Audit in project-related meetings.
3. Recommends and implements process improvements to ensure quality and efficiency.
4. Serve as lead contact for customer issues identified post production
5. In conjunction with business, investigate and communicate impact on Insurance products and decision criteria due to internal/external amendments.
6. Lead Project Manager function for project schedules and deliverables; ability to direct global project
7. Analyze data to produce meaningful metrics to management
8. Provides training, mentoring, and motivating a team of highly insightful and customer focused Analytics resources
9. Follows analytical and programming guidelines, standards, and best practices.
10. Defines thorough test requirements and objectives.
1. Bachelor’s degree in Mathematics, Statistics, Engineering, or related. Master's degree preferred.
2. At least 7+ years audit, data analytics, modeling development/validation or related experience
3. High degree of experience with analytical tools/programming languages such as Python, SQL, ECL, R, AWS, Azure, PowerBI, and MS office products
4. Excellent verbal and written communication skills; Clear and concise communication specifically of results, including the ability to distill complex data issues so they are understandable to non-data focused and non-technical executives.
5. Familiarity with the credit or insurance industry
6. Experience working with large datasets in various forms, including experience planning, conducting, and explaining the outcomes/results.
7. Strong team player, constructive and considerate of others’ inputs with the ability to positively influence others, diplomatic skills, confident speaker even in difficult situations
8. Ability to multi-task and efficiently negotiate changing priorities and responsibilities
9. Understanding of modeling techniques and potential impacts of related assumptions and limitations
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