Description

You will own the end-to-end lifecycle of AI models, from development to production-grade deployment and business system integration.

Responsibilities

• Develop and productionalize AI models, ensuring end-to-end deployment rather than handing off code to other teams.
• Build and scale data and AI pipelines using the Snowflake and Azure ecosystems.
• Implement RAG architectures and natural language processing tasks including text extraction, classification, and summarization.
• Integrate AI models into business systems such as Salesforce and PowerBI.
• Liaise with non-technical stakeholders to collect requirements and provide project updates.
• Apply model governance practices to ensure compliance and auditability in sensitive healthcare environments.

Required Skills

• 10+ years of experience as a Data Scientist with a track record of deploying multiple models into production.
• Deep hands-on experience with Python and the Azure Cloud ecosystem (Azure AI Search, Azure OpenAI, Azure AI Foundry, Azure SQL, and Azure Storage Blob).
• Expertise in Snowflake (Snowflake data warehouse, Snowpark, Snowflake Notebooks, and Streamlit).
• Proven experience implementing use cases using RAG architecture.
• Proficiency in SQL and Microsoft SQL Server for complex queries and data transformations.
• Experience handling PII/PHI and working within HIPAA and FHIR healthcare data standards.
• Hands-on experience with unstructured data and AI libraries such as Langchain, TensorFlow, PyTorch, scikit-learn, and spaCy.
• Familiarity with open-source AI Agentic frameworks like Crew.ai, Agnolo, Microsoft Auto-Gen, or browser-use.
• Experience scaling Proof of Concepts (POC) to full production environments.

Preferred Skills

• Familiarity with alternative programming languages including Julia, Haskell, R, Scala, or C++.
• Experience with data normalization, feature engineering, and data augmentation.

Key Skills

Education

Any Graduate