Senior Data Scientist
Tasks
- Build machine learning models for product quality prediction
- Build retrieval strategies hybrid search reranking contextual compression
- Communicate model behavior and tradeoffs to stakeholders
- Create production ML pipelines for manufacturing environments
- Design multi agent systems for predictive workflows
- Develop anomaly and drift detection monitoring
- Develop interactive data applications and APIs
- Develop retrieval augmented generation using RAG
- Implement hallucination detection and output validation
- Implement monitoring logging and observability for agentic systems
- Implement text analytics for quality narratives and feedback
- Mentor junior data scientists
- Optimize system performance latency token cost
Perks/Benefits
- N/A
Skills/Tech-stack
API Development | Agent memory | Agent systems | Agile | Anomaly Detection | Autoencoders | Concept drift | Concept drift detection | Data integration | Docker | Drift Detection | ETL | FastAPI | Flask | Function Calling | Git | Guardrails | Hybrid search | Imbalanced classification | Isolation Forest | Kubernetes | Language Models | Large Language Models | Machine Learning | Mathematics | Monitoring | Multi-Agent | Multi-Agent Systems | Observability | Prompt engineering | Python | Reranking | Retrieval-Augmented Generation | SQL | Statistics | Streamlit | Text Analytics | Time Series | Variational Autoencoders | Vector embeddings | Version control
Education
Roles
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