About this role
We're looking for a Senior 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. This isn't a reactive role. We expect you to come in with your own point of view, spot the problems worth solving, and go after them without waiting to be asked.
You'll need a genuine passion for complexity. The kind of messy, ambiguous problems where the question itself isn't fully formed yet. That's where you'll do your best work.
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:Proactively identify data-driven opportunities to improve the product — not just answer questions, but ask better ones
Leverage AI tools actively in your day-to-day work to work faster, go deeper, and raise the quality of your output
Design and run A/B tests across flows and features to build smarter, sharper products
Own analyses end-to-end: from framing the problem to presenting findings to the stakeholders who can act on them
Initiate and deliver reports on feature performance, experimentation results, and product health
Extract and analyze data using AI tools, Snowflake, Python, SQL, and other platforms
What you'll need:5+ years of experience as a data, product, or business analyst
A degree in Industrial Engineering, Mathematics, Statistics, or a related field
Practical experience with AI tools — this isn't optional, it's how we work
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 independence to drive your own work with clear communication
A real appetite for finding opportunities in ambiguous, underexplored areas
Full professional fluency in English
Ready to work in an office environment most days of the week
Enthusiasm about learning and adapting to the exciting world of AI – a commitment to exploring this field is a fundamental part of our culture