Senior Data Scientist
Tasks
- Build RAG pipelines for unstructured text
- Build client churn prediction models
- Design prompt strategies and evaluation frameworks
- Develop workforce management demand forecasting shift scheduling optimization and attrition models
- Drive end to end ML lifecycle from problem framing to monitored production systems
- Evaluate LLM outputs for relevance faithfulness and hallucinations
- Lead design develop and deploy ML and GenAI solutions
- Mentor junior data scientists and set technical standards
- Own architecture of LLM powered pipelines
- Present findings model behavior and tradeoffs to stakeholders
- Translate business problems into technical roadmaps
Perks/Benefits
Skills/Tech-stack
Attribution Modeling | CI/CD | Dash | Databricks | Demand Planning | Docker | DuckDB | Fine Tuning | Forecasting | GitHub Copilot | Hugging Face | LLM Fine-tuning | Langsmith | Language Models | Language Processing | Large Language Models | MLOps | Model Evaluation | Model Monitoring | Model Serving | Natural Language | Natural Language Processing | NoSQL | Optimization | Pandas | Polars | Prompt engineering | PyTorch | Python | Ragas | React | Retrieval-Augmented Generation | SQL | Shift scheduling | Streamlit
Education
N/A
Roles
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