Product Data Analyst

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.
The role
Nebius is looking for a Product Data Analyst. In this role, you’ll build and maintain analytical assets that support day-to-day decision-making across the product & business domains. You’ll work end-to-end: from shaping raw data into reliable datasets, to creating dashboards stakeholders actually trust to running deeper analyses that clarify what’s happening and what to do next. You’ll also help develop AI-assisted analytics tools that reduce manual reporting and surface anomalies early.
You’re welcome to work in our office in Amsterdam
Your responsibilities will include:
Master Product Analytics data and metrics & provide insights & consultancy to stakeholders and senior Management. from Product & Business domains. Act as their analytical thought partner and data focal point.
Dashboard development. Design, implement, document, and maintain interactive dashboards used by business stakeholders. Improve existing dashboards by optimizing usability, performance, and metric definitions.
Data engineering support. Contribute to ETL/ELT processes and data modeling: validate sources, monitor data freshness, improve data quality checks, and troubleshoot pipeline issues with clear root-cause writeups.
AI-driven analytics. Help design, test, and refine analytical AI agents that streamline reporting, standardize repetitive analysis, and proactively flag anomalies. Participate in evaluation (quality checks, false positives/negatives) and iterate based on feedback.
Exploratory and ad-hoc analysis. Translate business questions into analysis plans, apply appropriate statistical methods, and communicate findings clearly (including assumptions, limitations, and recommended actions). Turn recurring ad-hoc requests into reusable assets where possible.
Stakeholder collaboration. Clarify requirements, align on definitions (KPIs/metrics), and present results in a way that supports decisions—not just “interesting numbers.”
We expect you to have:
+4 years of experience as a product / business / data analyst