Our mission is to become the most loved insurance company in the world. As a customer-centric tech company, we created an insurance experience across Renters, Home, Pet, Car, and Life that is smart, instant, and delightful.

Our team of 1,200+ Lemonade Makers make it possible for over 2M customers throughout the US, UK and Europe to get coverage instantly, with nearly half of claims paid in a matter of seconds. Powered by AI and social impact, Lemonade is a purpose-built, technology-first insurance carrier. A Certified B-Corp, our commitment to social impact is embedded in every aspect of the company, and our Giveback program, which donates a percentage of leftover premiums to nonprofits selected by our community, has donated over $10M to organizations in need.

What you’re applying for:

We're looking for a Data Analyst to help turn Finance, Compliance, Insurance, and Actuarial questions into trusted answers and shipped analytical capabilities. You'll sit inside the FCIA team as the embedded data expert, working alongside Finance, Actuarial, Insurance Product, and Compliance leaders on the numbers that actually drive decisions — the metrics that shape how we price risk, manage reserves, close the books, and report to regulators, owned and governed by you, not passed off through a ticket queue.

We believe three things matter for every role at Lemonade: drive to push through challenges, efficiency that keeps standards high while moving fast, and adaptability that lets you pivot with data and AI insights. These aren't buzzwords, they're how we actually work.

Our AI-first approach isn't just a tagline either. We're building the future of insurance with AI at the center, and we need people who are genuinely excited to learn and grow alongside these tools.

In this role you'll

Own metric definitions for FCIA domains in the semantic layer — loss ratio, premium earning, reserves, unit economics by product and state — so every dashboard, query, and AI agent pulls from the same source of truth

Diagnose what's driving movement across loss ratios, reserve adequacy, premium pacing, and expense trends, and bring those findings into the Finance close cadence and monthly reviews where decisions actually get made

Build AI-assisted analytical tools — simulators, scenario models, agentic workflows — that let Finance and Actuarial partners explore "what if" questions without booking analyst time

Productionize recurring analyses so ad-hoc requests get replaced by governed, reusable capabilities that free the team up for higher-leverage work

Validate AI-generated outputs — SQL, summaries, recommendations — with the same rigor you'd apply to a junior analyst's work, because speed without judgment isn't useful

Partner across Engineering, Biz Ops, Insurance Product, Actuarial, and Finance on data projects that span the full policy lifecycle and financial close

What you'll need

3+ years in a data analytics role, ideally at a fast-growing consumer, fintech, or insurtech company

Advanced SQL and working proficiency in Python or R for analysis, scripting, and lightweight tooling-a MUST to qualify for this role

Hands-on experience with the modern analytics stack — Snowflake or equivalent, dbt, a BI tool (Looker preferred), and Git-based workflows

Fluency with AI-assisted development tools like Cursor, Claude, or Copilot — and the judgment to know when the output needs to be challenged

Strong communication skills: you can defend a metric definition under scrutiny and explain a complex finding to a non-technical Finance leader without losing either audience

A bachelor's degree in Mathematics, Statistics, Computer Science, or a related field — or equivalent practical experience

Ready to work in an office environment at least 3 days a week from our New York location