Head of Data
Tasks
- Adopt agentic AI frameworks
- Architect RAG pipelines
- Architect data platform
- Build AI agents and automation workflows
- Build feature engineering pipelines
- Define data quality monitoring and alerting
- Define data strategy
- Design GenAI and LLM use cases
- Develop and deploy machine learning models
- Drive technology selection for data tools
- Ensure fairness auditing and compliance
- Establish code review and CI CD
- Implement prompt management and monitoring for drift
- Implement real-time data streaming
- Implement responsible AI governance
- Lead ETL and ELT pipelines
- Lead collaboration with product and engineering
- Lead machine learning strategy
- Manage vector databases for semantic search
- Productionize AI features
- Run A B testing and continuous model improvement
- Set up LLMOps and model evaluation
- Unify data teams
Perks/Benefits
- Language learning budget
- Medical insurance
- Paid sick leave
- Paid vacation
- Professional education budget
- Remote work
- Wellness budget
Skills/Tech-stack
Autogen | Automl | CI/CD | Clean architecture | Code Versioning | Code review | Data Quality | Data Streaming | Data quality monitoring | Deep learning | ELT | ETL | Feature Engineering | GitHub Copilot | Gradient boosting | LLMOps | Langchain | Llamaindex | MLOps | MLflow | Machine Learning | Model Evaluation | Observability | PGVector | Pinecone | Prompt engineering | PySpark | Python | Quality monitoring | RAG | Real Time | Real-Time Data Streaming | Real-time Data | Regression | SQL | Scikit-learn | Software testing | Time Series | Vector Databases | Weaviate | Weights and Biases | XGBoost
Education
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