About the RoleWe're looking for a Data Analyst to partner closely with our Customer Success and GTM teams and turn data into decisions. You'll own the metrics that matter - acquisition, activation, retention, product usage, expansion, and revenue - and uncover the drivers behind them. You'll build the analyses that shape strategy, identify what influences customer success and growth, and help answer the critical questions: what's working, what isn't, and why.
This is a high-ownership, hands-on role for someone who loves digging into data, writes their own code, and ships analysis that changes what the business does next.
What You'll Do- Own GTM analytics end-to-end: define, instrument, and report on the funnel - from signup and activation through conversion, expansion, and churn.
- Proactively monitor key business metrics, investigate trends and anomalies, and surface actionable insights to stakeholders.
- Partner with other teams like Sales, Marketing and Product to scope questions, run analyses, and translate findings into clear recommendations.
- Dig into product usage and revenue data to surface insights on user behavior, cohorts, and monetization.
- Write production-quality SQL and Python to model data, automate pipelines, and run analyses at scale.
- Design and evaluate experiments (A/B tests) and measure the impact of GTM initiatives.
- Define metrics and a shared source of truth; bring rigor and clarity to how we measure success.
What We're Looking For (Must-Haves)- 5+ years of experience as a Data Analyst (or equivalent).
- 2+ years working in a SaaS company.
- Hands-on experience as a CS / Sales / Marketing / Business / Product analyst - you understand funnels, cohorts, conversion, retention, and the metrics that drive a SaaS business.
- Strong hands-on experience using Python for data analysis, experimentation, and data modeling in a production environment.
- Strong SQL and comfort working with large, messy datasets.
- Strong communication: you can turn analysis into a clear, compelling story for non-technical stakeholders.
- Statistical foundation for experimentation and causal inference.
- BSc in Statistics/Math/CS or equivalent
- Familiarity with modern data tooling (Snowflake/BigQuery, dbt, Airflow, BI tools like Omni/Looker/Tableau).
- Demonstrated ability to influence business strategy through data and drive alignment across cross-functional stakeholders.
Nice to Have- A track record of building your own projects - a GitHub profile, portfolio, side projects, or other evidence that you build things independently.
- Experience at an API-first, developer-focused, or PLG (product-led growth) company.
- Experience with product analytics platforms (PostHog, Amplitude, Mixpanel).
- Exposure to ML or working alongside data science teams.
- MSc in Statistic/Math/CS or equivalent
Key employee benefits in the US:- Health insurance: 100% company-paid medical, dental, and vision coverage for employees and families.
- 401(k) plan: Up to 4% company match with immediate vesting.
- Parental leave: 20 weeks paid for primary caregivers, 12 weeks for secondary caregivers.
- Remote work reimbursement: Up to $85/month for mobile and internet.
- Disability & life insurance: Company-paid short-term, long-term and life insurance coverage.
Pay TransparencyWe offer competitive compensation and benefits packages. Actual compensation will be determined based on job-related factors, including experience, skills, qualifications, the level at which the candidate is hired, and geographic location, consistent with applicable law.
Base Compensation Range
$109,500-$136,800 USD
Benefits & Perks:- Competitive compensation
- Career growth and learning opportunities
- Flexibility and ownership
- Collaborative and innovative culture
- Opportunity to work on impactful AI projects
- International environment and talented teams
