Data Scientist
Tasks
- Apply design thinking to build user centric AI products
- Build RAG pipelines for conversational AI
- Conduct experimentation and technical trade off decisions
- Design, build, and deploy agentic AI systems
- Fine tune prompt engineer evaluate and productionize LLMs
- Generate insights and data storytelling for executives
- Mentor and lead data science and AI initiatives
- Perform data wrangling and feature engineering
- Translate business objectives into data science problems
Perks/Benefits
- N/A
Skills/Tech-stack
AWS | Agent systems | Agentic AI | Autogen | Azure | CI/CD | Cloud platform | Cost Optimization | CrewAI | Deep learning | Explainability | Google Cloud | Google Cloud Platform | Hugging Face | Human-in-the-loop | LLMOps | Langchain | Langgraph | Language Models | Language Processing | Large Language Models | Llamaindex | MLOps | Machine Learning | Model Governance | Model Monitoring | Model versioning | Multi-Agent | Multi-Agent Systems | Natural Language | Natural Language Processing | Prompt engineering | PyTorch | Python | RAG Pipelines | Responsible AI | Retrieval-Augmented Generation | Risk Management | Scikit-learn | Statistical modeling | TensorFlow | The Loop
Education
Roles
Data Scientist | Principal | Principal Data Scientist | Scientist
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