Senior Data Scientist at Nebius

<div class="content-intro"><p><strong>About Nebius:</strong></p> <p>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.</p> <p>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.</p> <p>Listed on Nasdaq (NBIS) and headquartered in Amsterdam, we have a global footprint with R&amp;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&amp;D.</p></div><h3><strong><span data-ccp-props="{}">The role</span></strong></h3> <p data-start="77" data-end="436">Nebius is looking for a<span class="Apple-converted-space">&nbsp;</span><strong data-start="101" data-end="126">Senior Data Scientist</strong><span class="Apple-converted-space">&nbsp;</span>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.</p> <p data-start="438" data-end="675">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.</p> <p data-start="677" data-end="727">You’re welcome to work in our offices in Tel Aviv.</p> <p><strong><span data-contrast="auto"><span data-ccp-charstyle="Strong">Your responsibilities will include:</span></span></strong><span data-ccp-props="{&quot;134233117&quot;:true,&quot;134233118&quot;:true}">&nbsp;</span></p> <ul> <li><strong>Time series forecasting.</strong>&nbsp;Design, build, and maintain forecasting models (e.g., demand, usage, capacity). Evaluate performance using appropriate metrics and improve accuracy over time.</li> <li><strong>Classical ML modeling. </strong>Develop and deploy models using regression,Binary classifcatiom ,&nbsp;&nbsp;tree-based methods, and other well-established approaches where they provide the best trade-off between performance, interpretability, and maintainability.</li> <li><strong>Feature engineering &amp; data preparation. </strong>Build robust pipelines for data cleaning, transformation, and feature generation (including time-based features, seasonality, and external signals).</li> <li><strong>Model evaluation &amp; monitoring.</strong>Define evaluation frameworks, backtesting strategies, and monitoring to ensure models remain stable and reliable in production.</li> <li><strong>Production &amp; MLOps. </strong>Deploy models into production environments, collaborate on pipeline orchestration, and ensure reproducibility and version control.</li> <li><strong>Exploratory analysis. </strong>Analyze large datasets to identify patterns, anomalies, and drivers of change in time-dependent behavior.</li> <li><strong>Stakeholder collaboration. </strong>Work closely with business and product teams to define forecasting needs, align on success metrics, and translate model outputs into actionable insights.</li> <li><strong>Cross-domain contribution. </strong>Contribute to adjacent data science areas (e.g., LLM-based systems) as needed, ensuring shared ownership and continuity across team responsibilities.</li> </ul> <p><strong><span data-contrast="auto"><span data-ccp-charstyle="Strong">We expect you to have:</span></span></strong><span data-ccp-props="{&quot;134233117&quot;:true,&quot;134233118&quot;:true}">&nbsp;</span></p> <ul> <li data-start="1950" data-end="2028">Experience as a data scientist working in production environments (5+ years).</li> <li data-start="2031" data-end="2096">Experience with time series modeling and forecasting techniques.</li> <li data-start="2099" data-end="2176">Experience building reliable data pipelines and working with large datasets.</li> <li data-start="2179" data-end="2312">Experience with modern data science tools and ecosystems using Python (e.g., NumPy, Pandas, Scikit-learn, deep learning frameworks).</li> <li data-start="2315" data-end="2377">Strong SQL skills and experience working with large datasets.</li> <li data-start="2380" data-end="2447">Strong foundation in statistics and machine learning fundamentals.</li> <li data-start="2450" data-end="2594">Background in Computer Science, Statistics, Mathematics, Industrial Engineering, Economics, or a related field (Master’s degree or equivalent).</li> <li data-start="2597" data-end="2683">Demonstrated ability to take models from idea to production and ensure ongoing value.</li> <li data-start="2686" data-end="2783">Demonstrated ability to apply structured thinking and robust evaluation in forecasting problems.</li> <li data-start="2786" data-end="2882">Strong communication skills and ability to explain model outputs, uncertainty, and limitations.</li> <li data-start="2885" data-end="2934">Working knowledge of spoken and written English.</li> </ul> <p><strong><span data-contrast="auto"><span data-ccp-charstyle="Strong">It will be an added bonus if you have:</span></span></strong><span data-ccp-props="{&quot;134233117&quot;:true,&quot;134233118&quot;:true}">&nbsp;</span></p> <ul> <li data-start="2989" data-end="3050">Experience working in cloud environments (preferably Azure).</li> <li data-start="3053" data-end="3124">Experience with MLOps tools and production model lifecycle management.</li> <li data-start="3127" data-end="3196">Experience with workflow orchestration tools such as Apache Airflow.</li> <li data-start="3199" data-end="3289">Familiarity with LLM-based systems (e.g., evaluation, RAG pipelines) in applied settings.</li> </ul><div class="content-conclusion"><p><strong>Benefits &amp; Perks:</strong></p> <ul> <li>Competitive compensation</li> <li>Career growth and learning opportunities</li> <li>Flexibility and work-life balance</li> <li>Collaborative and innovative culture</li> <li>Opportunity to work on impactful AI projects</li> <li>International environment and talented teams</li> </ul> <p><strong>What's it like to work at Nebius:</strong></p> <p>Fast moving&nbsp;- Bold thinking&nbsp;- Constant growth&nbsp;- Meaningful impact&nbsp;- Trust and real ownership&nbsp;- Opportunity to shape the future of AI&nbsp;</p> <p><strong>Equal Opportunity Statement:</strong></p> <p>Nebius is an equal opportunity employer. We are committed to fostering an inclusive and diverse workplace and to providing equal employment opportunities in all aspects of employment. We do not discriminate on the basis of race, color, religion, sex (including pregnancy), national origin, ancestry, age, disability, genetic information, marital status, veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by applicable law.</p> <p>Applicants must be authorized to work in the country in which they apply and will be required to provide proof of employment eligibility as a condition of hire.&nbsp;</p> <p>If you need accommodations during the application process, please let us know.</p></div>