Senior Product Analyst, Data Scientist

Nebius Group

. Define core product and business metrics and build a single source of truth for Product, Finance, and Sales .

Posted 11/6/2026full-timeRemote • NetherlandsSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in analytics and data science with a strong focus on Python, SQL, and statistical analysis. Capable of translating complex data into actionable insights while collaborating cross-functionally to enhance product and commercial strategies.

Highest-signal resume keywords

Python ProgrammingSQL ProficiencyStatistical AnalysisCommercial AnalyticsCross-Functional Collaboration

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Data AnalysisCapacity ForecastingPricing Models DevelopmentCustomer SegmentationData-Driven RecommendationsStatistical ToolsLarge-Scale Dataset AnalysisAI-Assisted CodingProduction-Ready SolutionsUsage Pattern Analysis

Soft Skills

Proactive Working StyleClear CommunicationCommercial Judgment

Tools & Technologies

Distributed Data-Processing ToolsStatistical Tools

Industry Keywords

Self-Service CustomersCustomer HealthRetention RisksMonetizationLLM Inference Economics

Tech Stack

Tools & technologies

PythonSQL

About the role

Key responsibilities & impact

Define core product and business metrics and build a single source of truth for Product, Finance, and Sales
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 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

Requirements

What you’ll need

5+ years of experience in analytics or data science
Strong Python, SQL, and statistics
Hands-on experience analysing large-scale customer, product, and usage datasets using statistical, analytical, or distributed data-processing tools
AI-assisted coding as a default way of working, with the ability to guide, verify, and own the result
Ability to go from a question to a production-ready solution
Ability to turn complex data into clear recommendations
Strong commercial and product judgment, balancing customer value, monetization, growth, and profitability
Experience with pricing, packaging, monetization, or commercial analytics for technical or consumption-based products
Strong cross-functional collaboration across Product, Engineering, Data, Finance, Sales, and Operations
Hands-on and proactive working style in an ambiguous and technically complex environment
Applicants must be authorized to work in the country in which they apply and provide proof of employment eligibility
Familiarity with LLM inference economics, including tokens, throughput and latency, batching, and GPU costs (nice to have)

Benefits

Comp & 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
Fast moving
Bold thinking
Constant growth
Meaningful impact
Trust and real ownership
Opportunity to shape the future of AI