About the role
Veeam is the Data and AI Trust Company, specializing in helping organizations ensure their data and AI are fully understood, secured, and resilient to enable the acceleration of safe AI at scale. As the market leader in both data resilience and data security posture management, Veeam is built for the convergence of identity, data, security, and AI risk. Headquartered in Seattle with offices in more than 30 countries, Veeam protects over 550,000 customers worldwide, who trust Veeam to keep their businesses running. Join us as we go fearlessly forward together, growing, learning, and making a real impact for some of the world’s biggest brands.
About
the Role At Veeam, data drives every strategic decision we make. As a Senior Data Science Engineer , you'll join our Revenue Intelligence team, where you'll design and deliver scalable data science, machine learning, and AI solutions that enable smarter business decisions across the organization. This is an opportunity for a hands-on engineer who enjoys solving complex business problems with modern AI technologies, building intelligent applications, and working across cross-functional teams to transform data into actionable insights. You'll help shape the future of Revenue Intelligence by leveraging machine learning, large language models (LLMs), and advanced analytics to create innovative, production-ready solutions.
What You'll Do Design, develop, and deploy scalable data science, machine learning, and AI solutions that drive business value. Build production-ready ML pipelines, from feature engineering and model development through deployment and monitoring. Develop AI-powered applications using modern frameworks such as Streamlit and integrate Large Language Models (LLMs) into business workflows. Design and maintain Retrieval-Augmented Generation (RAG) solutions, knowledge bases, and AI agents using structured and unstructured enterprise data. Perform quantitative and qualitative analyses to identify trends, generate insights, and support strategic decision-making. Partner with business stakeholders to translate complex business challenges into scalable AI and analytics solutions. Collaborate with data engineers, software engineers, analysts, and product teams on cross-functional initiatives. Improve existing data science processes, identify automation opportunities, and promote engineering best practices. Contribute to technical documentation, knowledge sharing, and continuous improvement initiatives. What You'll Bring 4+ years of professional experience in Data Science, Machine Learning, AI Engineering, or a related field. Strong programming skills in Python and SQL. Experience designing and deploying scalable machine learning solutions, including feature engineering, model evaluation, deployment, and MLOps practices. Hands-on experience with Large Language Models (LLMs), prompt engineering, Retrieval-Augmented Generation (RAG), Model Context Protocol (MCP), or similar AI frameworks. Solid understanding of data engineering concepts, including ETL/ELT pipelines, data modeling, governance, and storage optimization. Experience with Databricks, PySpark, or distributed data processing platforms. Familiarity with software engineering best practices, including APIs, version control, testing, CI/CD, and deployment workflows. Experience with business intelligence and visualization tools such as Tableau, Power BI, or Qlik. Excellent analytical thinking, problem-solving, communication, and technical writing skills. Experience using Agile project management tools such as Jira, Confluence, or Trello.