Costa Rica onlyVeeam, the #1 global market leader in data resilience, believes businesses should control all their data whenever and wherever they need it. Veeam provides data resilience through data backup, data recovery, data portability, data security, and data intelligence. Based in Seattle, Veeam protects over 550,000 customers worldwide who trust Veeam to keep their businesses running. Join us as we move forward together, growing, learning, and making a real impact for some of the world’s biggest brands. The future of data resilience is here - go fearlessly forward with us.
About the Role
We’re looking for a Data Science Engineer with 7+ years of experience to join the Revenue Intelligence team at Veeam. This role is ideal for someone who thrives in a fast-paced environment, enjoys building scalable data solutions, and is passionate about driving business impact through analytics, machine learning, and AI. You’ll work closely with cross-functional teams to turn data into actionable insights and intelligent applications.
What You’ll Do
- Design and implement data science, machine learning, and AI solutions to support strategic decision-making
- Perform deep-dive quantitative and qualitative analyses to validate business hypotheses and drive improvements
- Contribute to cross-functional initiatives involving data science, ML, and AI engineering use cases
- Develop knowledge bases from structured and unstructured data to support RAG systems and AI agents
- Build data-driven applications (e.g., Streamlit) to enable internal access to AI-powered capabilities
- Partner with stakeholders to deliver actionable insights and recommendations
- Continuously improve processes and identify opportunities for automation and efficiency
Technologies You’ll Work With
Python, SQL, Machine Learning & AI Frameworks, Databricks / PySpark, Data Visualization Tools (Streamlit, Tableau, Power BI, Qlik)
What You’ll Bring
- 7+ years of professional experience in data science, analytics, or machine learning roles
- Strong proficiency in Python and SQL
- Experience building scalable data science solutions (feature engineering, model training, evaluation, deployment, MLOps)
- English Bilingual
- Solid understanding of data engineering concepts (ETL/ELT, data modeling, pipelines, governance)
- Experience integrating LLMs into production systems (prompt engineering, RAG, AI agents)
Bonus Skills
- Experience with software engineering best practices (APIs, testing, version control, deployment)
- Hands-on experience with Databricks or PySpark
- Familiarity with data visualization platforms and storytelling with data
- Experience using project management and collaboration tools (Jira, Trello, Confluence)
- Strong technical writing and documentation skills
What You’ll Get
- 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
Please note that any personal data collected from you during the recruitment process will be processed in accordance with our Recruiting Privacy Notice.
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By submitting your application, you acknowledge that the information provided in your job application and any supporting documents is complete and accurate to the best of your knowledge. Any misrepresentation, omission, or falsification of information may result in disqualification from consideration for employment or, if discovered after employment begins, termination of employment.
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