Lead Data Scientist
New
J
JobgetherData Science AI
United StatesFull-TimeLead
Salary136,000 - 192,000 USD per year
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Job Details
- Required Skills
- PythonSQLMachine LearningSnowflakeData modelingDatabricksPrompt EngineeringLLM
Requirements
- Bachelor’s, Master’s, or PhD in Data Science, Computer Science, Statistics, Applied Mathematics, Engineering, or related quantitative discipline.
- Strong Python development skills with experience creating production-ready analytics, AI, and data engineering solutions.
- Hands-on experience building RAG solutions including vector databases, embeddings, and semantic search technologies.
- Experience with enterprise AI technologies including LLM APIs, prompt engineering, and AI-driven workflow automation.
- Experience integrating large language models through platforms such as OpenAI, Snowflake Cortex, Databricks AI, or Anthropic.
- Strong SQL and data-platform expertise including data modeling and transformation.
- Experience working with cloud environments such as Snowflake, Databricks, or Microsoft Fabric.
- Knowledge of machine learning, statistical analysis, and AI evaluation frameworks.
- Experience deploying AI/analytics solutions via APIs, web applications, or enterprise reporting platforms.
Responsibilities
- Design, develop, and optimize Retrieval-Augmented Generation (RAG) solutions combining LLMs with enterprise knowledge stores and operational data.
- Build and maintain AI knowledge architectures including metadata frameworks, vector stores, and semantic models.
- Develop reusable AI skills, agents, and copilots to automate analytical workflows, root-cause analysis, and insight discovery.
- Lead AI cost-optimization initiatives through effective retrieval patterns, model selection, and token-management strategies.
- Partner with engineering teams to integrate and deploy AI capabilities across business applications and analytics environments.
- Apply best practices for prompt engineering, hallucination mitigation, and AI evaluation to improve solution reliability.
- Contribute to analytics modernization by identifying opportunities for Generative AI applications.
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