Principal Data Scientist, Vice President
Tasks
- Architect and operationalize LLM solutions
- Build RAG knowledge base solutions
- Create model evaluation and benchmarking frameworks
- Define AI and ML roadmap
- Deploy and manage ML model lifecycle
- Ensure model governance and regulatory compliance
- Establish error taxonomy and explainability
- Implement anomaly detection and Responsible AI
- Implement embeddings and vector search
- Integrate knowledge graphs
- Integrate models with enterprise platforms
- Lead design and development of machine learning solutions
- Lead enterprise AI experimentation and monitoring
- Lead model validation testing and monitoring
- Mentor and develop data science teams
- Partner with business and engineering stakeholders
- Perform prompt engineering and fine-tuning
- Productionize AI models with MLOps and LLMOps
Perks/Benefits
- Employee networks
- Flexible work/life support
- Inclusive development opportunities
- Paid volunteer days
Skills/Tech-stack
AWS | Anomaly Detection | Apache Spark | Azure | Benchmarking | CI/CD | Databricks | Embeddings | Experiment tracking | Explainable AI | Feature Engineering | Fine Tuning | Graph reasoning | Keras | Knowledge graphs | LLMOps | Langchain | Language Processing | Llamaindex | MLOps | Model Evaluation | Model Monitoring | Model Risk Management | Model Validation | Model risk | Model versioning | Natural Language | Natural Language Processing | Prompt engineering | PyTorch | Python | RAG | Responsible AI | Retrieval-Augmented Generation | Risk Management | SQL | Scikit-learn | TensorFlow | Vector Databases | Vector Search
Education
Bachelor of Engineering | Bachelor of Science | Master of Science
Roles
Data Scientist | Principal | Principal Data Scientist | Scientist
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