Senior Data Analyst

The role

Nebius is looking for a Senior Data Analyst who will act as a trusted analytical partner to business and product stakeholders. You will work end-to-end: from shaping raw data into reliable datasets, to creating dashboards stakeholders trust, to running deeper analyses that clarify what’s happening, why it’s happening, and what to do next.
This role requires strong technical foundations, but also mature business judgment. You will be expected to understand business context, structure ambiguous problems, challenge assumptions constructively, and turn analysis into practical recommendations. You should be comfortable working with incomplete information, changing priorities, and complex stakeholder needs — bringing clarity where things are messy.
You will also contribute to developing AI-assisted analytics tools that reduce manual reporting, support better decision-making, and surface anomalies early.
You’re welcome to work in our office in Amsterdam.

Your responsibilities will include:

Dashboard development. Design, implement, document, and maintain interactive dashboards used by business stakeholders. Improve existing dashboards by optimizing usability, performance, and metric definitions. Ensure dashboards are reliable, actionable, and aligned with business priorities.
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, including quality checks and false positives/negatives, and iterate based on feedback.
Exploratory and ad-hoc analysis. Translate business questions into structured 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 and metrics, and present results in a way that supports decisions — not just “interesting numbers”. Build trusted relationships with stakeholders and help them interpret data in the context of business trade-offs.
Problem structuring and decision support. Work through ambiguous or poorly defined problems, break them down into manageable analytical questions, and help stakeholders make decisions despite uncertainty.
Analytical best practices. Help raise the quality of analytics work by improving documentation, reviewing metric definitions, sharing best practices, and supporting less experienced colleagues where relevant.

We expect you to have:

• Significant experience as a Data Analyst, Senior Data Analyst, Business Analyst, Product Analyst, or in a similar analytical role.
• Strong proficiency in Python and SQL, and confidence using Excel when it is the most efficient tool.
• Solid grounding in statistics and analytical thinking, including descriptive statistics, hypothesis testing, and regression fundamentals.
• Experience producing clear data visualizations and communicating analytical findings in plain language.
• Strong attention to data quality and detail, including validating definitions, identifying inconsistencies, and implementing data checks.
• Demonstrated ability to translate business questions into structured analysis and actionable insights.
• Solid business acumen, including the ability to understand business drivers, connect analysis to commercial or operational impact, and prioritize analytical work based on value.
• Strong problem-solving skills, with the ability to break down complex or unclear questions, form hypotheses, test assumptions, and identify practical next steps.
• Comfort with uncertainty and ambiguity, including the ability to move work forward when requirements are incomplete, data is imperfect, or priorities shift.
• Strong written and verbal communication skills, including explaining technical concepts to non-technical audiences.
• Strong stakeholder management skills, including the ability to clarify needs, challenge assumptions constructively, and align stakeholders around definitions and conclusions.
• Working knowledge of spoken and written English.

It will be an added bonus if you have:

• Experience with BI tools such as Tableau, Power BI, Looker, or Superset.
• Familiarity with modern data stacks such as dbt, Airflow, BigQuery, Snowflake, or PostgreSQL.
• Experience with experiment analysis, cohort analysis, or funnel metrics.
• Experience working in cloud infrastructure, AI/ML, SaaS, developer tools, or another technical product environment.
• Experience mentoring other analysts or contributing to analytics standards, documentation, and best practices.