Senior Data Scientist- Finance & Spend, Data Labs

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Skills you'll use

Who can apply

• 5+ years of experience in knowledge engineering, semantic data systems, applied AI, or data science in industry, research labs, or advanced academic environments.
• Master's or PhD in Computer Science, Applied Mathematics, Statistics, Engineering, or a related quantitative field
• Hands-on experience designing enterprise ontologies and semantic models; proficiency in at least one graph query language (SPARQL, Cypher, or GQL); understanding of trade-offs between RDF triple stores and property graph databases.
• Hands-on experience with modern GenAI systems RAG, embeddings, vector databases, semantic retrieval, and enterprise knowledge grounding. Strong Python and SQL skills with production-grade development practices; experience with ML libraries such as PyTorch, TensorFlow, or scikit-learn.
• Proven track record deploying and operating AI/ML solutions in production including handoff, lifecycle support, and continuous improvement.
• Experience with big data infrastructure and cloud environments Databricks or equivalent, plus at least one major cloud (AWS, Azure, or GCP).
• Excellent communication and stakeholder management skills, with the ability to work cross-functionally in agile environments.

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