Data Scientist, Lifetime Value at Root
We believe a large part of building an effective insurance company can be solved with a principled quantitative framework. We are committed to the rigorous development and effective deployment of modern statistical machine learning methods to problems in the insurance industry.
We are looking for Data Scientists to join our Lifetime Value (LTV) Analytics team. As part of this team, you will create models that predict conversion, retention, and/or loss cost. The team also builds and maintains tools that bring these models together to predict the lifetime value (and other related key metrics) of Root customers. You’ll work closely with partners across finance, marketing, pricing, product management, and other data science teams to support different business cases and optimize business outcomes.
We are hiring various levels of Data Scientists. Candidates with outstanding skills and experience will be considered for more senior-level roles.
What you’ll be doing.
- Applying principled methods to quantitative insurance challenges, estimating customer lifetime value
- Building data processing pipelines to quickly iterate on research ideas and put them into production
- Creating reports and dashboards displaying insights from models and monitoring model performance
- Effectively communicating insights from complex analyses
- Taking end-to-end ownership of problem domains and continuously improving upon quantitative solutions
- Leverage internal and external data sources to engineer novel features that enhance the accuracy of our models
What we’re looking for.
- Advanced degree in a quantitative discipline and/or 3+ years of applying advanced quantitative techniques to problems in industry
- Strong demonstrable knowledge of topics such as Bayesian statistics, machine learning, and numerical optimization
- Demonstrated experience applying statistical machine learning methods to enhance the decision making of an organization
- Exceptional communicator and storyteller
- Strong programming skills with experience using modern python or R packages. Experience with GBM libraries such as XGBoost or CatBoost is preferred
- Experience sourcing data for modeling from a star schema data warehousing architecture and feature engineering using SQL
Exceptional candidates may have experience in one or more of the following.
- Insurance rating plan development (personal lines auto insurance preferred)
- Insurance conversion and/or retention (churn) modeling experience
- Taking models to production and monitoring their performance
- Causal inference from observational data
- Generalized linear models, Tweedie distribution
- Using models to inform digital advertising or lead bidding decisions
- Experience using AWS cloud infrastructure (ec2, s3, Sagemaker)
Who we are.
Root Insurance is the nation’s first licensed insurance carrier powered entirely by mobile. We were founded on the belief that the services you need for everyday life should serve you better. That’s why we base insurance coverages on you, not your demographic. It’s the way insurance should be. And it’s all conveniently in an app.
What draws people to Root.
We’re a venture-backed technology company. Our early success is in large part due to our unwavering standards in hiring. We recognize that our product is only as good as the people building and promoting it. We look for individuals who find solutions by going through the cycle of ideation to implementation with curiosity, rigor, and a highly analytical lens. Ask anyone who works here and you’ll hear similar reasons for why they joined:
Autonomy. For assertive self-starters, the opportunities to contribute are limitless.
Impact. By challenging the way it’s always been done, we solve problems that have a big impact on our business.
Collaboration. We encourage rich discussion and civil debate at every turn.
People. We are inspired by the collection of crazy-smart people around us.