The role

Nebius is looking for a Senior Data Scientist (Applied AI / LLM) to design, build, and deploy production-grade AI systems based on large language models. You will focus on turning LLM capabilities into reliable, measurable business solutions, while also contributing to predictive modeling across different business domains.

Your work will include building evaluation frameworks, improving model accuracy, and developing agent-based systems that automate analytical and data workflows (e.g., data quality monitoring). The role emphasizes production readiness, robustness, and real business impact—not experimentation.

You’re welcome to work in our office in Tel Aviv.

Your responsibilities will include: 

• LLM system development. Design and deploy LLM-based solutions (e.g., RAG pipelines, agent workflows) for real business use cases.
• Evaluation & reliability. Build evaluation frameworks to measure accuracy, consistency, and failure modes of LLM systems. Continuously improve performance based on real-world usage.
• Agent-based automation. Develop agentic solutions to automate workflows such as data quality checks, anomaly detection, and reporting.
• Applied predictive modeling. Apply classical ML and statistical methods to business domains such as HR and Finance (e.g., forecasting, classification, risk modeling).
• Production & MLOps. Deploy and maintain models in production, ensuring monitoring, versioning, and scalability.
• Stakeholder collaboration. Translate business needs into AI/ML solutions and communicate trade-offs, risks, and performance clearly.
• Cross-domain contribution. Contribute to adjacent areas (e.g., forecasting models) to ensure team redundancy and shared ownership of critical workflows.

We expect you to have: 

• Experience as a data scientist or applied ML practitioner (5+ years).
• Experience building and deploying LLM-based systems in production.
• Experience working in production environments with model monitoring and iteration.
• Experience with modern data science and ML ecosystems using Python.
• Experience working with large datasets and strong SQL skills.
• Understanding of LLM evaluation, prompt design, and system behavior.
• Strong foundation in statistics and machine learning fundamentals.
• Demonstrated ability to deliver production-grade AI systems end-to-end.
• Demonstrated ability to translate business needs into AI/ML solutions and communicate clearly.
• Working knowledge of spoken and written English.

It will be an added bonus if you have: 

•  Experience with RAG architectures and retrieval systems.
• Experience designing or working with agent-based workflows.
• Experience with MLOps tools and production ML systems.
• Experience working in cloud environments (preferably Azure).

The role

Nebius is looking for a Senior Data & Business Analyst to lead analytics and business health indicators across our operational and company-wide domains. This is a senior individual contributor role combining strategic thinking, deep hands-on analytical execution, and strong cross-functional business partnership. You’re welcome to work in our office in Tel Aviv.

The role requires the ability to operate at two levels simultaneously: understanding the full business picture while diving deep into complex datasets and technical execution. You will work closely with Operations, Finance, and other cross-functional teams to improve efficiency, transparency, and decision-making across the organization.

Your responsibilities will include: 

• Own end-to-end analytics for core operational processes.
• Define, build, and maintain company-level operational and business health KPIs.
• Translate ambiguous, cross-functional business questions into structured analytical frameworks.
• Write advanced, high-performance SQL to extract, model, and analyze complex datasets.
• Lead deep-dive analyses to uncover operational inefficiencies, financial impact, and process gaps.
• Connect data across systems and explain upstream and downstream business impact.
• Independently identify high-impact problems worth solving, not only respond to requests.
• Drive cross-functional analytical initiatives at a company-wide level.
• Present insights, trade-offs, and recommendations to senior leadership.
• Synthesize complex findings into concise executive-level narratives.
• Influence decisions and drive measurable impact based on data.
• Act as a central analytical partner across multiple business domains.
• Lead initiatives and move stakeholders forward without direct authority.

We expect you to have: 

• Experience as a Data Analyst, Business Analyst, or similar analytical role.
• 5+ years of experience in data or business analytics within operational or financial domains.
• Expert-level SQL skills, including complex joins, CTEs, window functions, and performance optimization.
• Experience working with ERP or operational systems data.
• Experience operating at both high-level strategic view and deep hands-on analytical execution.
• Experience leading cross-functional initiatives and influencing stakeholders without direct authority.
• Experience operating at a company-wide level, not only within a single function.
• Demonstrated ability to deliver measurable business impact such as cost reduction, efficiency gains, process improvements, or revenue optimization.
• Strong executive-level presentation and communication skills.
• Demonstrated ability to challenge assumptions and influence senior stakeholders using data.
• High ownership, independence, and strong execution mindset.
• Working knowledge of spoken and written English.

It will be an added bonus if you have: 

• Experience with NetSuite or similar ERP systems.
• Experience with operational workflow or spend management tools.
• Experience with BI tools such as Looker, Tableau, or Power BI.
• Experience partnering with Finance or FP&A teams.
• Background in operational efficiency or cost optimization initiatives.

The role

Nebius is looking for a Senior Data Scientist to build and deploy time series forecasting and classical machine learning models that support core business planning and operational decisions. You will own problems end-to-end, from data exploration and feature engineering to model deployment and monitoring, working with large-scale, real-world datasets.

The role emphasizes strong statistical thinking, robust modeling, and production reliability over experimentation with trendy frameworks. Your work will directly impact forecasting accuracy, resource planning, and key business metrics.

You’re welcome to work in our offices in Tel Aviv.

Your responsibilities will include: 

• Time series forecasting. Design, build, and maintain forecasting models (e.g., demand, usage, capacity). Evaluate performance using appropriate metrics and improve accuracy over time.
• Classical ML modeling. Develop and deploy models using regression,Binary classifcatiom ,  tree-based methods, and other well-established approaches where they provide the best trade-off between performance, interpretability, and maintainability.
• Feature engineering & data preparation. Build robust pipelines for data cleaning, transformation, and feature generation (including time-based features, seasonality, and external signals).
• Model evaluation & monitoring.Define evaluation frameworks, backtesting strategies, and monitoring to ensure models remain stable and reliable in production.
• Production & MLOps. Deploy models into production environments, collaborate on pipeline orchestration, and ensure reproducibility and version control.
• Exploratory analysis. Analyze large datasets to identify patterns, anomalies, and drivers of change in time-dependent behavior.
• Stakeholder collaboration. Work closely with business and product teams to define forecasting needs, align on success metrics, and translate model outputs into actionable insights.
• Cross-domain contribution. Contribute to adjacent data science areas (e.g., LLM-based systems) as needed, ensuring shared ownership and continuity across team responsibilities.

We expect you to have: 

• Experience as a data scientist working in production environments (5+ years).
• Experience with time series modeling and forecasting techniques.
• Experience building reliable data pipelines and working with large datasets.
• Experience with modern data science tools and ecosystems using Python (e.g., NumPy, Pandas, Scikit-learn, deep learning frameworks).
• Strong SQL skills and experience working with large datasets.
• Strong foundation in statistics and machine learning fundamentals.
• Background in Computer Science, Statistics, Mathematics, Industrial Engineering, Economics, or a related field (Master’s degree or equivalent).
• Demonstrated ability to take models from idea to production and ensure ongoing value.
• Demonstrated ability to apply structured thinking and robust evaluation in forecasting problems.
• Strong communication skills and ability to explain model outputs, uncertainty, and limitations.
• Working knowledge of spoken and written English.

It will be an added bonus if you have: 

• Experience working in cloud environments (preferably Azure).
• Experience with MLOps tools and production model lifecycle management.
• Experience with workflow orchestration tools such as Apache Airflow.
• Familiarity with LLM-based systems (e.g., evaluation, RAG pipelines) in applied settings.