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

• Equal pay
• Hybrid work model
• Inclusive work environment
• Skill development opportunities

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