Data Scientist
Tasks
- Assess accuracy latency cost safety
- Build evaluation frameworks
- Build retrieval-augmented generation pipelines
- Build scalable modeling patterns and tooling
- Build statistical models
- Collaborate on technical discovery and architecture
- Communicate results to non-technical stakeholders
- Conduct data audits and modeling workshops
- Create agent evaluation rubrics
- Create executive ready business cases demos and rollout plans
- Deploy models for business impact
- Design machine learning models
- Develop tool using agent workflows
- Engineer features
- Harden prototypes into production ready solutions
- Monitor model drift
- Perform exploratory data analysis
- Prototype AI agents and copilots
- Select models
- Support responsible AI governance and privacy standards
- Translate business problems into modeling initiatives
Perks/Benefits
Skills/Tech-stack
AI Foundry | APIs | AWS Bedrock | Agents SDK | Azure AI | Azure AI Foundry | BigQuery | ChatGPT | Claude | Copilot Studio | Databricks | Embeddings | Evaluation harnesses | Google Gemini | Google Vertex | Google Vertex AI | HubSpot | Jupyter | LLM Evaluation | Langchain | Langgraph | Language Models | Large Language Models | MLOps | Machine Learning | Microsoft Copilot | Model Deployment | Model Monitoring | N8n | OpenAI | OpenAI APIs | OpenAI Agents | OpenAI Agents SDK | PGVector | Pinecone | Prompt engineering | PyTorch | Python | RAG | Retrieval-Augmented Generation | SQL | Salesforce | Scikit-learn | Snowflake | Statistics | TensorFlow | Vector Databases | Vertex AI | Weaviate | XGBoost | Zapier
Education
N/A
Roles
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