Data Science Leader, Spend
Tasks
- Align AI investments with business objectives
- Apply deep learning and neural networks to learn from data
- Build and scale ontology driven enterprise intelligence
- Define AI technical strategy and team priorities
- Design agentic multi agent orchestration workflows
- Design and optimize RAG pipelines and semantic retrieval
- Design knowledge graphs and semantic layers
- Develop AI ML architecture and platform strategy
- Drive AI initiatives from concept to production
- Establish model governance and responsible AI practices
- Integrate knowledge graphs with machine learning and generative AI
- Lead mentoring and growing data science teams
- Select machine learning algorithms and prepare training datasets
- Train machine learning models and evaluate accuracy
Perks/Benefits
- N/A
Skills/Tech-stack
Agent Orchestration | Deep learning | Embedding Models | Entity Resolution | Entity modeling | Hybrid search | Keyword search | Knowledge graphs | LLMOps | Lakehouse | Lifecycle Management | MLOps | Machine Learning | Metadata Management | Model Governance | Model Lifecycle | Model Lifecycle Management | Neural Networks | Ontology Engineering | RAG | Responsible AI | Semantic Retrieval | Semantic Search | Statistics | Taxonomies | Vector Search
Education
Regions
Countries
States
Cities
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