Product Data Analyst
Lemonade · TLV
- On site
- Fulltime
- TLV
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Subject: Interested in the Product Data Analyst role at Lemonade
Hi Taylor — I came across the Product Data Analyst opening and wanted to reach out directly. I've spent the last few years doing exactly this kind of work, and Lemonade stood out because…
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About the role
We're looking for a Product Data Analyst to help us find the opportunities hiding in our data and turn them into real product improvements.
You'll be part of the Analytics team, embedded in product decisions from early question to final recommendation. You will be tackling analytical questions, monitoring the metrics that matter, and surfacing insights that actually change how we build
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:
Collaborate with Analytics, Product, and Data teams to sharpen business decisions.
Initiate analyses and generate reports for feature tracking, experiments, and product health monitoring
Design A/B tests across our flows and processes to build better products
Analyze data using Snowflake, Python, and other platforms
Present key findings to stakeholders across the company, turning data into clear, actionable direction
Map new data domains and identify signals that push our product forward
What you’ll need:
3+ years of experience as a data, product, or business analyst, ideally at a fast-growing consumer company
A degree in Industrial Engineering, Mathematics, Statistics, or a related field
Strong SQL skills and hands-on experience with BI tools (Looker, Tableau, Mixpanel, or similar)
Familiarity with A/B testing best practices and comfort working with complex datasets
The ability to work fluidly across product managers, data engineers, and data scientists, and to communicate technical findings clearly in English
Ready to work in an office environment most days of the week