The position.

We believe a large part of building an effective insurance company can be solved with a principled quantitative framework and a pragmatic data science approach of applying the right tool to the job in a way that balances accuracy and complexity. We are committed to the rigorous development and effective deployment of modern methods to problems in the insurance industry.

We are looking for a Data Science Engineer, Forecasting to join our Data Science Forecasting team. As part of this team, you will build tools to translate data science model predictions into forecasted business metrics. In this role, you will use software engineering skills paired with modern quantitative methods and best practices to deploy robust production models used in our forecasting process. You will work closely with Data Scientists, Data Analysts, and members of the Finance team to understand the detailed performance of our business and contribute to principled and sustainable growth.

The ideal candidate will have a software engineering background as well as experience with predictive modeling techniques in production on a data science team.

What you'll achieve.

  • Scope, build, and test a forecasting application in Python
  • Collaborate with stakeholders across the forecasting pipeline including data engineers, data scientists, and financial analysts to ensure data integrity and consistency
  • Engineer production solutions for deploying the forecasting engine and adjacent machine learning models to end users.
  • Identify opportunities for new machine learning models to support the forecasting process, and either implement these models or help scope these models for implementation by a data scientist
  • Contribute to forecast and model diagnostics and monitoring with an emphasis on scalable self-serve analytics
  • Think critically in your work to ensure functionality aligned with business goals

What we're looking for.

  • 3-5+ years of experience in software engineering, 2+ years experience in data science or data analytics
  • Deep understanding of multiple programming paradigms and languages—including Python—and strong front-end experience
  • Solid knowledge of databases, SQL, version control tools, and agile software development practices
  • Strong cross-functional communication and a disciplined approach to testing for system reliability and reasonableness of outputs
  • Familiarity with complex financial modeling in Excel is a plus

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