Data Analyst (Customer Success)
About Tavily We're building the infrastructure layer for agentic web interaction at scale. Our API is designed from the ground up to power Retrieval-Augmented Generation (RAG) and real-time reasoning in AI systems. By connecting LLMs to high-quality, trustworthy web content, we help developers build agents that are not only intelligent - but also informed. We work with some of the most innovative teams in AI - from small startups shaping the ecosystem to the largest enterprises deploying AI at scale. Whether it’s powering sales assistants, research copilots, or internal knowledge tools, we’re the missing link between LLMs and the real world.
About the Role
We'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 Transparency We 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