Hello, we’re Flare! We are reimagining how attorneys and clients work together. We are obsessed with building solutions that empower attorneys and consumers through the legal journey. Funded by leading VC firms, we are an industry leader in legal technology. Our platform simplifies the delivery of complex legal services while providing ease and clarity to clients and attorneys throughout the process. With a global team that brings a fresh perspective, Flare is revolutionizing the way legal services are delivered. We’re a team of creative problem-solvers who want to make the world a better place. Join us.
At Flare, every product decision starts with understanding our users.
Every feature we launch, experiment we run, and product investment we make generates new questions: Where do users succeed? Where do they struggle? What drives engagement? What creates friction? And where should we invest next?
That's what this role is for.
As a Senior Product Analyst, you'll serve as a strategic partner to Product, Engineering, and Design, helping teams answer the questions that shape our product roadmap. You'll own key product metrics end-to-end, uncover the behavioral insights behind them, and turn complex data into clear, actionable recommendations that drive smarter product decisions.
AI is a core part of how we work. We use it throughout our analytics workflow to automate repetitive tasks, accelerate analysis, and improve efficiency—freeing you to focus on solving complex product problems, asking better questions, and generating insights that create real business impact.
Partner with Product Managers, Engineers, and Designers to answer the questions that matter most. You'll uncover behavioral insights, identify opportunities for growth, and influence the decisions that shape our product roadmap.
Own the Metrics That Matter
Take end-to-end ownership of your product domain's metrics. You'll define and evolve KPIs, ensure data accuracy, and help teams make confident, data-driven decisions they can trust.
Drive Experimentation
Design and analyze experiments from hypothesis to recommendation. You'll partner with cross-functional teams to define success metrics, evaluate A/B tests, and distinguish meaningful product impact from statistical noise.
Build Decision-Making Infrastructure
Create dashboards and self-service reporting that teams rely on every day, while delivering deeper analyses that go beyond the numbers. Your work will make it easier for Product, Engineering, and leadership to understand what's happening, why it's happening, and what to do next.
Leverage AI to Increase Impact
Use AI throughout your workflow to accelerate SQL development, automate repetitive analysis, improve documentation, and explore data more efficiently. You'll combine AI with strong analytical judgment to ensure every insight is accurate, reliable, and actionable.
Raise the Bar for Analytics
Contribute to the way the team works by sharing reusable code, AI prompts, documentation, and best practices. You'll help build a scalable analytics culture where knowledge is shared and everyone moves faster together.
Requirements
You have 4+ years of experience in Product Analytics, Data Science, or a similar analytical role.
You enjoy partnering with Product Managers, Engineers, and Designers to solve complex product problems and influence decisions with data.
You're comfortable working through ambiguity, turning broad business questions into structured analyses and clear recommendations.
You take ownership of the metrics you own, ensuring they're accurate, actionable, and trusted across the organization.
You have hands-on experience with experimentation, including A/B testing and cohort analysis, and understand how to distinguish meaningful insights from statistical noise.
You build dashboards and reports that help teams monitor performance, answer everyday questions, and make better decisions.
You're proficient in SQL and Tableau.
You use modern AI tools to accelerate your work, while applying strong analytical judgment to validate results and ensure quality.
Nice to have
Experience working in a fast-growing technology company, ideally with a consumer-facing product.
Experience using Git and VS Code in a collaborative analytics or engineering environment.
Strong foundation in statistics, including experimentation, causal inference, or data modeling.
Experience contributing to data infrastructure, shared analytics repositories, or reusable analytics tooling.