United States onlyRoot was founded on the belief that car insurance is broken, and we set out to change it. We’re harnessing the power of technology to revolutionize this archaic, complicated industry. Using machine learning and mobile telematic platforms, we’ve built one of the most innovative insurtech companies in the world.
The Opportunity
We believe that a disruptive insurance company must have a principled quantitative framework at its foundation. At Root, we are committed to the rigorous development and effective deployment of modern statistical machine learning (ML) methods to problems in the insurance industry.
A Data Scientist II at Root is responsible for the end-to-end development of statistical methods and algorithms. This includes taking high-level business challenges, translating them into a concrete, quantitative framework, and shepherding solutions from R&D into production. Data Scientists typically work on cross-functional teams, regularly engaging with the members of various departments including Product, Engineering, and State Management.
The Interventions data science team leverages ML techniques to target interventions that improve customer lifetime value, whether via mitigation of risk (e.g., fraudulent claims, bad debt) or by enhancing conversion and retention in our most profitable customer segments. We are looking for a Data Scientist II who will monitor and improve our suite of ML models, seek out new applications for ML to create business impact, and conduct rigorous experiments to validate new targeted interventions.
Salary Range: $116,664 - $145,830 (Bonus and LTI Eligible)
Root is a “work where it works best” company. This means we will support you working in whatever location that works best for you across the US.
How You Will Make an Impact
- Create robust predictive models for use in targeted interventions, using modeling techniques such as LightGBM
- Apply principled methods to translate model segmentation gains to improvements in key financial metrics
- Learn the required tools to get the job done, e.g., AWS (EC2, SageMaker, S3), Git, etc.
- Build data science pipelines to quickly iterate on research ideas and put them into production
- Effectively communicate insights from complex analyses
- Take end-to-end ownership of problem domains and continuously improve upon quantitative solutions
What You Will Need to Succeed
- Advanced degree in a quantitative discipline (PhD preferred) and/or 2+ years of applying advanced quantitative techniques to problems in industry
- Strong demonstrable knowledge of topics such as statistical modeling, machine learning, and numerical optimization
- Exceptional communicator and storyteller with strong data visualization skills
- Strong programming skills with experience using modern packages in Python
- Experience with databases and SQL
- Demonstrated experience building, validating, and applying statistical machine learning methods to real world problems
- Ability to work independently with a strong ownership mentality, taking initiative to find, prioritize, and be accountable for the highest impact work
- Ability to frame functional problem statements for the next 1-2 months, consistently making good decisions about the right path to follow in a well-defined problem space
- Preferred but not required:
- Experience using version control (Git) and cloud computing (AWS)
- Insurance industry experience
As part of Root's interview process, we kindly ask that all candidates be on camera for virtual interviews. This helps us create a more personal and engaging experience for both you and our interviewers. Being on camera is a standard requirement for our process and part of how we assess fit and communication style, so we do require it to move forward with any applicant's candidacy. If you have any concerns, feel free to let us know once you are contacted. We’re happy to talk it through.
Please see our Privacy Notice available HERE for more information on how we process your personal data.
