About Nebius:
Nebius is leading a new era in cloud infrastructure for the global AI economy. We are building a full-stack AI cloud platform that supports developers and enterprises from data and model training through to production deployment, without the cost and complexity of building large in-house AI/ML infrastructure.
Built by engineers, for engineers. From large-scale GPU orchestration to inference optimization, we own the hard problems across compute, storage, networking and applied AI.
Listed on Nasdaq (NBIS) and headquartered in Amsterdam, we have a global footprint with R&D hubs across Europe, the UK, North America and Israel. Our team of 1,500+ includes hundreds of engineers with deep expertise across hardware, software and AI R&D.
About Tavily
In a rapidly evolving world, trust in AI depends on AI agents being grounded in fresh, verified real-world data. Search is the foundation that makes this possible.
Tavily provides the search and intelligence layer that powers AI agents and retrieval systems with trustworthy, real-time information. We work with some of the most innovative teams in AI, from fast-growing startups to global enterprises, helping them build agents that are not only intelligent but informed.
About the Role
We're looking for a Senior Product Analyst to drive product decisions with data. You'll research how developers and companies discover, adopt and get value from Tavily and find the drivers behind them. You'll work as a thought partner to Product, R&D and leadership and shape what we build next and why.
This is a senior, high-ownership role. You take a question from start to finish: you frame the problem, build the data you need, run the analysis or model, and come back with a clear recommendation.
You are expected to understand the need and show people results they didn't even knew they wanted or needed and be an integrational part in decision making. You'll work closely with the analysts on the team and with Product, Engineering, Growth and GTM.
What You'll Do
• Own product analytics end-to-end: define, instrument and measure the product funnel, from first API call through activation, feature adoption, retention and conversion to paid.
• Drive product decisions: work with PMs and R&D leads to set success metrics, size opportunities, prioritize the roadmap, and measure the impact of what we ship.
• Uncover the drivers behind top-level KPIs: which behaviors, use cases, endpoints and product experiences predict activation, retention and expansion.
• Design, run and evaluate experiments (A/B tests, onboarding flows, pricing and packaging changes) and apply advanced statistical models when needed.
• Build the data you need: model raw product, usage and billing data into trusted, reusable datasets with SQL, dbt and Python and more.
• Apply predictive and statistical modeling (segmentation, propensity, forecasting, classification and clustering) where it sharpens product decisions.
• Proactively monitor key product metrics, investigate trends and anomalies, and surface insights stakeholders can act on.
• Set the standard for how we measure product success: metric definitions, a shared source of truth and analytical rigor across teams.
What We're Looking For
• 5+ years of experience as a Product Analyst, Data Analyst or Data Scientist, including at least 2 years in a product-facing role.
• 2+ years in a SaaS or tech product company, with deep understanding of funnels, cohorts, engagement, retention and monetization.
• A proven record of driving product decisions through data: you've shaped roadmaps, launches or strategy, not just reported on them.
• Comfort working with large, messy, event-level datasets.
• Strong hands-on experience using Python for data analysis, experimentation and data modeling in a production environment.
• Strong statistical foundations.
• Demonstrated ability to influence business strategy through data and drive alignment across cross-functional stakeholders, including executive leadership.
• Strong communication: you can turn complex analysis into a clear, compelling story and a concrete recommendation.
• Experience with modern data tooling (Snowflake/BigQuery, dbt, Airflow, and BI tools like Omni/Looker/Tableau).
• BSc in Statistics / Math / CS / Industrial Engineering or equivalent.
Nice to Have
• Experience at an API-first, developer-focused or PLG company.
• Hands-on experience building and deploying ML models.
• Familiarity with LLMs / AI tooling, and using AI agents to speed up your own analytical work.
• Evidence that you build things on your own: a GitHub profile, portfolio, side projects or publications.
• MSc in Statistics / Math / CS or equivalent.
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
What's it like to work at Nebius:
Fast moving - Bold thinking - Constant growth - Meaningful impact - Trust and real ownership - Opportunity to shape the future of AI
Equal Opportunity Statement:
Nebius is an equal opportunity employer. We are committed to fostering an inclusive and diverse workplace and to providing equal employment opportunities in all aspects of employment. We do not discriminate on the basis of race, color, religion, sex (including pregnancy), national origin, ancestry, age, disability, genetic information, marital status, veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by applicable law.
Applicants must be authorized to work in the country in which they apply and will be required to provide proof of employment eligibility as a condition of hire.
If you need accommodations during the application process, please let us know.
Skills Required
- 5+ years of experience as a Product Analyst, Data Analyst, or Data Scientist, including at least 2 years in a product-facing role
- 2+ years of experience in a SaaS or technology product company
- Deep understanding of funnels, cohorts, engagement, retention, and monetization
- Demonstrated record of driving product decisions through data, including roadmaps, launches, or strategy
- Experience working with large, messy, event-level datasets
- Strong hands-on Python experience for data analysis, experimentation, and production data modeling
- Strong statistical foundations
- Ability to influence business strategy and align cross-functional stakeholders, including executives
- Strong communication skills for translating complex analysis into recommendations
- Experience with modern data tooling, including Snowflake or BigQuery, dbt, Airflow, and BI tools such as Omni, Looker, or Tableau
- BSc in Statistics, Mathematics, Computer Science, Industrial Engineering, or equivalent
- Experience at an API-first, developer-focused, or product-led growth company
- Hands-on experience building and deploying machine learning models
- Familiarity with LLMs, AI tooling, and AI agents
- GitHub profile, portfolio, side projects, or publications demonstrating independent building
- MSc in Statistics, Mathematics, Computer Science, or equivalent
Nebius Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Nebius and has not been reviewed or approved by Nebius.
-
Fair & Transparent Compensation — Pay is considered competitive or good across many roles, with overall sentiment leaning positive. While experiences vary by team and location, compensation frequently stands out as a strength.
-
Flexible Benefits — Work arrangements are described as remote-friendly with hybrid options and flexibility across time zones. Some roles reference home-office stipends that support distributed work.
-
Healthcare Strength — Company materials and job postings describe comprehensive employer-paid medical, dental, and vision coverage for employees and families. Details may vary by country and entity.
Nebius Insights
What We Do
Cloud platform specifically designed to train AI models
