Data Scientist II

SUMMARY

The Data Scientist II will work with actuarial, marketing, operations, and/or our media and technology teams to develop machine learning models and data-driven research that reveals key insights. These insights drive the strategic direction of corporate initiatives. This position will be responsible for solving important business problems through data mining and advanced analytics.

The Data Scientist II demonstrates a strong working knowledge of statistical and machine learning techniques and the ability to learn new ones. As a complement to modeling expertise, this position is also expected to be comfortable building robust data pipelines from transactional systems typical of the financial services industry to support the development and deployment of ML models.

ESSENTIAL DUTIES AND RESPONSIBILITIES include the following. Other duties may be assigned.

• Translate business problems into analytical questions for investigation
• Extract data from source systems to create refined, reusable datasets that further enable predictive models and advanced analytics
• Leverage proprietary and third-party datasets in novel ways to derive insights, optimize processes, and drive strategy
• Explore and add to our growing repository of experimentation methods and statistical techniques that could sharpen or speed up decision-making processes
• Develop robust ML pipelines that are built with monitoring and retraining in mind
• Consult with DevOps and other technical teams on the proper way to integrate predictive models into our applications
• Help business stakeholders understand the value of ML models, how they work, and how we can refine them to further our goals

QUALIFICATIONS

To perform this job successfully, an individual must be able to perform each essential duty satisfactorily. The requirements listed below are representative of the knowledge, skill, and/or ability required.

• Professional experience in a data or analytical role or Master's degree (computer science, mathematics, statistics, and engineering) with an emphasis on predictive modeling.
• 2-5 years of professional experience in an analytical role. No actuarial exams required.
• Experience solving real problems using advanced analytics
• Ability to tell a story with data; strong time and project management skills with the ability to manage detail work and communicate project status effectively to all levels
• Strong Python knowledge required; familiarity with PySpark and Databricks is a plus
• Property/casualty insurance background or jewelry industry experience is helpful