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Home Actuarial Leader

Lemonade

Home Actuarial Leader

Lemonade

Remote

·

Remote

·

Full-time

·

1w ago

Compensation

$175,000 - $195,000

Benefits & Perks

Equity

Remote Work

Equity

Remote Work

Required Skills

P&C Actuarial

Pricing Models

Python

R

SQL

Machine Learning

Team Leadership

We’re looking for a driven Actuarial Leader who is ready to lead a talented team while building the most innovative home insurance on the market! This role is critical as we accelerate our product's growth across new states and expand our analytical capabilities with cutting-edge machine learning.

You’ll be spearheading the development and implementation of advanced pricing models for our home product, managing rate levels, and bringing actuarial discipline to all facets of Lemonade—from distribution and underwriting to claims, compliance, and finance. You will leverage competitive data and data science to optimize our customers’ experiences and ensure fairness and accuracy in pricing, directly impacting our profitability and mission-driven growth.

In this role you’ll

  • Own state rating plans and rate indications for Lemonade home

  • Lead the development and integration of predictive modeling projects while working closely with the Data Science team

  • Develop the rates and pricing strategy for product expansions into new states

  • Assist in the design and development of internal pricing software for advanced analytics to support real-time decision making and scalable growth

  • Craft rate filing support for new machine learning models

  • Recommend pricing and underwriting actions based on ongoing monitoring of results

  • Build a knowledge base of competitor rating strategies and the overall competitive landscape

  • Manage and develop a team of high-performing analysts

  • Further your actuarial education through CAS exams and industry research while applying learnings on the job

What you'll need

  • 7+ years of P&C actuarial experience; FCAS preferred

  • 2+ years leading and managing a team

  • B.S. in Actuarial Science, Mathematics, Statistics, or a related field

  • Proficiency in data science programming languages such as R or Python (preferred), and database query tools such as SQL

  • Proficient with predictive modeling concepts, including supervised and unsupervised machine learning approaches such as GLMs, decision trees, gradient boosting machines, random forests, and clustering.

  • Prior personal lines pricing experience is a definite plus

  • Ability to work and manage in a remote environment

  • Enthusiasm about learning and adapting to the exciting world of AI – a commitment to exploring this field is a fundamental part of our culture

Please note that we are unable to sponsor applicants for work visas

Unfortunately, we cannot consider applicants from these states; Colorado, California, Montana, Hawaii, New Mexico and Puerto Rico.

Lemonade's US base salary range for this full-time position is $175,000 -$195,000 + equity + benefits. Our salary ranges are determined by role, level, and location. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Speak to your recruiter to hear more about the specific salary range for your preferred location.

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About Lemonade

Lemonade

Lemonade

Public

Insurance company.

201-500

Employees

New York City

Headquarters

$1.2B

Valuation

Reviews

2.8

7 reviews

Work Life Balance

1.2

Compensation

2.0

Culture

1.1

Career

1.5

Management

1.0

15%

Recommend to a Friend

Pros

Remote work options available

First job experience opportunity

Intensive feedback for learning

Cons

Toxic management and micromanagement

Poor work-life balance and long hours

High employee turnover

Salary Ranges

15 data points

Junior/L3

Senior/L5

Junior/L3 · Statistical Reporting Analyst

1 reports

$80,301

total / year

Base

$69,826

Stock

-

Bonus

-

$80,301

$80,301

Interview Experience

1 interviews

Difficulty

4.0

/ 5

Duration

21-35 weeks

Interview Process

1

Application Review

2

Phone Screen

3

Technical Interview

4

Behavioral Interview

5

Final Round

Common Questions

Technical Knowledge

Behavioral/STAR

Past Experience

Case Study