Actuarial Associate, Car
Job description
About the role
This role guides how car insurance prices are set and monitored, using data and modeling to support fair, scalable decisions. The team relies on clear methods and careful judgment to handle complex pricing questions.
Data roles turn raw information into decisions. Analysts query databases and build dashboards. Data scientists build models that predict outcomes. Data engineers build the pipelines that move and store data. All three work closely with business teams and need a mix of statistics, coding, and communication. Nearly every modern company runs on data teams, from startups to banks. A strong portfolio of past analyses matters more than degrees in many hiring decisions.
Key facts
What you'll do
Ownership of rating plans sharpens how car prices are set and communicated to customers and regulators. Analysis of predictive models with Data Science shapes how methods are tested and used in production. Rate filing materials support new machine learning models and help stakeholders understand how prices are derived. Monitoring of pricing and underwriting results uncovers chances to refine rules and improve accuracy. Cross-functional collaboration with Underwriting, Product, Claims, and BI turns findings into aligned actions and decisions. Advancement of actuarial credentials feeds new insights and techniques directly into daily work.
Requirements
Four or more years of P&C actuarial experience, preferably in personal lines pricing, grounds the work in real practice. Five CAS exams show depth in actuarial methods and judgment. A Bachelor's degree in Actuarial Science, Mathematics, Statistics, or a related field is required. Working knowledge of data science programming languages such as R or Python, plus SQL proficiency, supports analysis and modeling. Familiarity with predictive modeling concepts, including GLMs, decision trees, gradient boosting machines, random forests, and clustering, is necessary. A strong sensitivity to model transparency and ethics guides how methods are designed and used. Eagerness to learn and grow alongside AI tools is essential for how the team operates. Ability to work independently in a remote environment keeps the work flowing without close supervision.
Practical notes
Work is fully remote, and tools enable collaboration across locations. Team members in this role must work from locations where Lemonade can employ them, and they must follow local rules and workflows. Employment is at-will, and pay and duties may vary by location and background. Typical interview steps
Data interviews commonly include a SQL or coding exercise, a statistics question, and a case study. Candidates may be asked to design a metric, interpret an experiment, or build a small model. Some companies give a take-home analysis. Expect questions about past projects and the business impact of your work. Interviewers often evaluate how you communicate uncertainty and business impact, not only the math. Bringing a clean write-up of a past analysis to the interview is well received.
Good to know
The role focuses on pricing, modeling, and monitoring for car insurance using data and AI. Actuarial methods, model transparency, and ethics are central to the work. Collaboration across functions is common, and continuous learning alongside AI tools is expected. The position uses competitive data, data science methods, and rating systems to support scalable pricing decisions.
Career growth
Data careers grow toward senior analyst, staff data scientist, or data engineering lead. Many professionals specialize in machine learning, analytics, or infrastructure. Cross-functional work with product and engineering teams becomes more important at senior levels. The field changes quickly, so continuous learning is part of the job. Professionals who can translate numbers into decisions tend to advance fastest.
About the company
Sweet lemon drink forms the core identity. This drink may include bubbles or stay still. Many cultures claim their own style. Global versions exist with different recipes. Current focus stays on this simple beverage. Hiring aims to strengthen this drink centered vision. Teams explore tastes and traditions. Open roles seek creative minds. Candidates should care about drink basics. Join efforts to define how this drink appears in different markets today.