The posting, in Nebius Group's own words
archived Nov 6, 2026About 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:
In Token Factory analytics there is no split into product analysts, ML engineers and data engineers. Each person owns a question end to end: builds the data, runs the analysis, and comes back with a recommendation that changes a decision.
Read the full posting ↓
Your responsibilities will include:
- Define core product and business metrics and build a single source of truth that Product, Finance, and Sales can rely on. - Build a comprehensive view of self-service customers, including usage patterns, customer health, satisfaction, retention risks, unmet needs, and growth opportunities. - Translate customer demand and commercial plans into capacity forecasts and support capacity allocation decisions. - Measure effective capacity utilization and identify opportunities to improve the commercial value of available capacity. - Develop and evaluate pricing and packaging models, including guaranteed capacity, on-demand pricing, commitments, clawback mechanisms, and provisioned throughput units. - Provide data-driven recommendations for the self-service and managed offerings, including customer segmentation, pricing, and capacity. - Partner with Product, Engineering, Applied AI, Finance, and Sales to turn insights into concrete product and operational improvements.
We expect you to have:
- 5+ years of experience in analytics or data science. - Strong Python, SQL, and statistics: you understand the code and the methods you use. - Hands-on experience analysing large-scale customer, product, and usage datasets using statistical / analytical or distributed data-processing tools. - AI-assisted coding as your default way of working: you guide it, verify it, and own the result. - The ability to go from a question to a production-ready solution. - The ability to turn complex data into clear recommendations. - Strong commercial and product judgment, with the ability to balance customer value, monetization, growth, and profitability. - Experience with pricing, packaging, monetization, or commercial analytics for technical or consumption-based products. - Strong cross-functional collaboration skills across Product, Engineering, Data, Finance, Sales, and Operations. - A hands-on and proactive working style, with the ability to operate effectively in an ambiguous and technically complex environment.