Data Scientist - Applied AI & ML
Leawood, Kansas, United States
USD 100K-140K (estimate) Mid-level Full Time
Tasks
- Apply privacy by design and minimize PII exposure
- Build evaluate improve AI powered products including LLM agents and RAG workflows
- Define instrumentation requirements and measurement plans
- Define model metrics labels thresholds and retraining strategies
- Design and analyze experiments including A B tests and holdouts
- Design evaluation frameworks for AI systems
- Ensure auditable deletion retention and compliance processes
- Implement MLOps and LLMOps release gates and automated quality checks
- Improve retrieval quality through embeddings chunking and ranking
- Maintain golden datasets and regression tests
- Monitor AI systems for quality latency cost drift and hallucination risk
- Own improve machine learning models for scoring forecasting and planning
- Perform feature engineering across business data sources
- Productionize datasets and features in Microsoft Fabric
- Quantify ROI and produce decision ready readouts
- Run red team testing and failure analysis
- Support BI and analytics with SQL notebooks and Power BI
Perks/Benefits
- N/A
Skills/Tech-stack
A/B | A/B Testing | APIs | Anomaly Detection | Azure Key Vault | B testing | CI/CD | Classification | Cosmos DB | Embeddings | Experiment design | Feature Engineering | Forecasting | Git | Key Vault | LLM | LLMOps | Langchain | Language Processing | Llamaindex | Logging | MLOps | Machine Learning | MongoDB | Monitoring | Natural Language | Natural Language Processing | Pandas | Prompt engineering | Python | RAG | Regression | Retrieval-Augmented Generation | SQL | Scikit-learn | Semantic Search | Vector Search
Education
Bachelor of Engineering | Bachelor of Science | Master of Science
Roles
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