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Nebius is a Nasdaq-listed cloud infrastructure company building a full-stack AI cloud platform for developers and enterprises. The company supports the entire AI lifecycle—from data and model training through production deployment—without requiring customers to build large in-house AI/ML infrastructure. Headquartered in Amsterdam with 1,500+ employees and R&D hubs across Europe, North America, and Israel, Nebius owns the hard problems in compute, storage, networking, and applied AI.
You will join the Data Analytics function within Nebius's CISO department, working alongside a senior BI Developer focused on Tableau dashboards. The team supports both cybersecurity risk and broader operational and PMO metrics, collaborating with security, GRC, PMO, IT, and leadership stakeholders.
In this role, you will explore complex datasets to identify patterns, anomalies, and root causes, turning them into actionable insights. You'll investigate changes in key metrics, form hypotheses, and run structured deep-dives to uncover underlying drivers. You will segment and compare data across dimensions (distributions, percentiles, baselines) to surface meaningful differences and outliers. You'll research and assess new data sources and APIs from an analytical perspective—evaluating availability, quality, limitations, and analytical value.
You will use SQL to extract, join, and analyze data from multiple sources, and Python (pandas) for exploratory analysis, data manipulation, and automating recurring analyses. You'll help define and refine KPIs and metrics alongside stakeholders, applying analytical rigor to both cybersecurity risk metrics and operational/PMO KPIs (program delivery, resourcing, process efficiency). You will leverage AI-assisted tools to speed up exploratory analysis, coding, and documentation while validating and owning outputs. You'll identify data-quality issues and work with relevant teams to resolve them, create lightweight visualizations to communicate findings, and present insights and recommendations to technical and non-technical stakeholders.
REQUIREMENTS
Must have:
- 2–4 years of professional experience as a Data Analyst or in a similar hands-on analytical role
- Strong SQL skills: joins, CTEs, window functions, aggregations, working across multiple data sources
- Hands-on Python experience for data analysis, including pandas (e.g., building repeatable analysis notebooks or automating recurring reports)
- Strong exploratory data analysis skills and comfort working with unfamiliar or messy datasets
- Ability to identify trends, anomalies, and outliers, and investigate drivers behind metric changes through root-cause analysis
- Strong attention to data quality and discipline to validate findings before drawing conclusions
- Ability to turn ambiguous business questions into structured analytical approaches
- Clear communicator, comfortable presenting findings and recommendations to non-technical audiences
- Strong written and verbal English
Strong advantage:
- Experience in a CISO, SOC, GRC, cybersecurity, or security operations environment
- Familiarity with security metrics (vulnerability management, incident response, access management, risk, compliance KPIs)
- Experience analyzing data from security tools (SIEM, EDR, IAM, vulnerability management, ticketing platforms)
- Knowledge of frameworks such as ISO 27001, NIST CSF, or SOC 2
Nice to have:
- Familiarity with statistical methods used in exploratory analysis and anomaly detection
- Experience with Tableau, Power BI, or another BI/visualization platform
- Experience with cloud platforms (Azure, AWS, GCP)
- Familiarity with data transformation concepts or tools such as dbt
- Comfort using AI/LLM-based tools to accelerate analysis, coding, or documentation
