Staff Data Scientist - Applied AI Engineering

THE SKILLL SET:

• Experience: 10+ years in Data Science or Machine Learning, with a proven track record of shipping AI products at scale (Staff/Lead experience preferred).
• Core ML & Stats: Deep expertise in Classical ML (XGBoost, Causal Inference), Time-Series Forecasting, and Deep Learning fundamentals. You understand the math behind the models, not just how to import libraries.
• Generative AI Mastery: Practical experience building with LLMs in production. Proficiency with modern frameworks (LangChain, LlamaIndex, DSPy), vector databases (Pinecone, Milvus), and techniques like Fine-tuning (PeFT/LoRA) and RAG optimization.
• Engineering First: Expert-level proficiency in Python and SQL. You write production-ready code (modular, tested, typed) and are comfortable working within a larger software engineering ecosystem (Git, Docker, CI/CD wrappers).
• System Design: Ability to design end-to-end ML systems. You can articulate trade-offs between model complexity, inference cost, and latency, and make architectural decisions that stand the test of time.
• Education: MS or PhD in Computer Science, Statistics, Physics, Math, or equivalent quantitative field is preferred.