Senior Data Scientist
Tasks
- Build GenAI solutions using LLMs and retrieval
- Communicate AI strategy and results to stakeholders
- Deploy models with MLOps collaboration
- Design and deploy models for security anomaly and fraud detection
- Develop scalable AI APIs services and workflows
- Establish experimentation and evaluation practices
- Evaluate emerging AI technologies
- Lead AI projects from concept to production
- Mentor data scientists and review technical approaches
- Partner on privacy security ethical and responsible AI practices
- Provide technical ownership for applied AI and data science initiatives
- Set technical direction for reliable maintainable AI systems
Perks/Benefits
- Diversity and inclusion working groups
- Flexible working practices
- Paid volunteer time off
- Parental leave
Skills/Tech-stack
Agentic Workflows | Artificial Intelligence | CI/CD | Code review | Cross-validation | Data Drift | Data Governance | Data drift monitoring | Databricks | Drift monitoring | Embeddings | Evaluation metrics | Experiment tracking | Git | Ground Truth | Ground Truth Evaluation | Hugging Face | LLM APIs | Langchain | Langgraph | Language Models | Large Language Models | Lifecycle Management | MLflow | Machine Learning | Model Lifecycle | Model Lifecycle Management | Model versioning | Observability | OpenAI | Prompt engineering | Python | Retrieval-Augmented Generation | Scikit-learn | Semantic Kernel | Serving | Structured Output | Testing | Tool use
Education
Bachelor of Engineering | Bachelor of Science | Master of Science | PhD
Roles
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