Senior Product Analyst (Agentic Search)

Nebius · Israel · по договорённости

Компания
Nebius
Город
Israel
Зарплата
по договорённости
Уровень
senior
Формат
full_time
Иностранная компания
нанимает русскоязычных

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 ex

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