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.

The Pricing R&D team is looking for a Data Analyst to continuously improve our risk segmentation. In this role, you will work closely with Data Scientists and Actuaries to increase the maturity of our model development lifecycle through iterative improvements to both pre- and post-deployment analytics. You will leverage third-party data to enhance our pricing models through creating novel, industry-leading segmentation. At the center of the pricing-underwriting ecosystem, you will create robust monitoring frameworks for KPIs to assess the performance of our business and recommend data-driven improvements.

The ideal candidate will have deep analytical and business acumen, with strong programming skills and high quantitative aptitude.

Responsibilities:

• Generate and interpret descriptive statistics to make business recommendations
• Standardize and automate the analytics pipeline for use across the pricing organization
• Forecast the impact of proposed pricing model updates to KPIs
• Analyze the business impact of segmentation updates to recommend pricing model improvements
• Perform deep-dive analyses into third-party data to generate novel segmentation opportunities
• Inform underwriting strategy through identifying trends and building robust fraud analytics

Qualifications:

• 1+ years of experience in data analytics
• Strong programming skills in R or Python
• Advanced skills in SQL with the ability to write complex and optimized queries
• Analytical mindset, with strong problem solving and critical thinking skills
• Exceptional communicator and storyteller

Preferences:

• 3+ years of experience in P&C insurance analytics
• Experience in R or Python package development
• Experience with large-scale analytics on AWS platforms