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.
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.
- 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.
- Experience developing AI copilots, autonomous agents, or conversational AI applications.
- Exposure to cloud-native AI and machine learning platforms.
- Familiarity with vector databases, embeddings, and semantic search technologies.
- Experience working in Revenue Operations, Sales Analytics, or Business Intelligence environments.
- Knowledge of future AI, OpenAI, or similar generative AI ecosystems.
- Two weeks of paid vacation, 12 statutory holidays, plus 4 extra global VeeaMe Days for self-care and 24 paid volunteer hours annually through Veeam Cares
- Paid parental leave: 8 days for fathers, 122 days for birthing parents, 92 days for adoptive parents
- Medical, dental, and vision coverage fully funded through INS Premium for employees and dependents
- Mental health support, therapy sessions, and virtual care via our Employee Assistance Program
- Retirement and social security contributions through Costa Rica’s statutory programs
- Life insurance equal to 24x monthly salary, plus disability and funeral coverage
- Daily cafeteria subsidy
- Fertility, adoption, and surrogacy support, plus 24 paid volunteer hours through Veeam Cares
- Opportunities to learn and grow through on-demand libraries (LinkedIn Learning, O’Reilly), mentoring, workshops, and learning events like our annual Global Day of Learning
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Veeam Software is an equal opportunity employer and does not tolerate discrimination in any form on the basis of race, color, religion, gender, age, national origin, citizenship, disability, veteran status or any other classification protected by federal, state or local law. All your information will be kept confidential.
Personal data collected during the recruitment process will be processed in accordance with our Recruiting Privacy Notice, which explains how your information is collected, used, and handled in connection with hiring activities. By applying for this position, you consent to this processing.
By submitting your application, you confirm that the information provided, including any supporting documents, is complete and accurate to the best of your knowledge. Any misrepresentation, omission, or falsification may result in disqualification from consideration or, if discovered after employment begins, termination of employment.
Skills Required
- 4+ years of professional experience in Data Science, Machine Learning, AI Engineering, or related field
- Strong programming skills in Python
- Strong programming skills in 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), or Model Context Protocol (MCP)
- 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
- Experience developing AI copilots, autonomous agents, or conversational AI applications
- Exposure to cloud-native AI and machine learning platforms
- Familiarity with vector databases, embeddings, and semantic search technologies
- Experience working in Revenue Operations, Sales Analytics, or Business Intelligence environments
- Knowledge of future AI, OpenAI, or similar generative AI ecosystems
Veeam Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Veeam and has not been reviewed or approved by Veeam.
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Healthcare Strength — Healthcare coverage is comprehensive with options that include employee-only no-cost tiers, plus mental-health support through an assistance program. Feedback suggests these offerings compare well in tech.
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Leave & Time Off Breadth — Time off includes unlimited PTO in the U.S., paid company holidays, quarterly company-wide recharge days, and paid volunteer time. Feedback suggests team norms influence how fully this flexibility is utilized.
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Strong & Reliable Incentives — Sales and pre-sales roles feature meaningful on-target earnings with competitive base and variable structures. Feedback suggests these plans provide strong upside for high performers.
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What We Do
Veeam provides a single platform for modernizing backup, accelerating hybrid cloud and securing data. Veeam has 400,000+ customers worldwide, including 82% of the Fortune 500 and 69% of the Global 2,000. Veeam’s 100% channel ecosystem includes global partners, as well as HPE, NetApp, Cisco and Lenovo as exclusive resellers, and boasts more than 35K transacting partners worldwide.
