Data Analyst
Lemonade Inc - NYC, New York, United States
Posted May 19, 2026
Benefits
- Parental leave
- Not verified
- Non-birth-parent leave
- Not verified
- Family-building benefits
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- Fertility benefits: Not verified
- Adoption assistance: Not verified
- Surrogacy assistance: Not verified
- Mental health support
- Not verified
- Relocation assistance
- Not verified
- Childcare support
- Not verified
- Learning budget
- Not verified
- Verification
- Not verified last checked Jun 13, 2026
- Salary
- Not verified not verified - source not recorded; timestamp not recorded
- 401(k) match
- Listed Source: EMPLR_CONTRIB_INCOME_AMT. source Last checked Jun 13, 2026.
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Schedule
- Shift type
- Not verified
- Weekend work
- Not verified
Application
- Cover letter
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- Assessment
- Not verified
- Deadline
- Not stated
Where they hire
State eligibility is not yet verified.
About this role
Data Analyst NYC, New York, United States 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
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