Description

Own data governance, quality standards, and AI-driven analytics workflows.

This role is hybrid.

Responsibilities

• Design and deploy statistical models and ML algorithms for business insights, including forecasting and exploratory data analysis on sales and operations.
• Own data definitions, lineage, and quality standards; develop data dictionaries and glossaries to ensure AI outputs trace to trusted sources.
• Define and monitor data quality rules, triage issues, and automate metadata management and lineage tracking.
• Design and deploy AI agents and LLM-powered workflows for governance and analytics using agent-based frameworks.

Required Skills

• 5+ years of experience in Data Science, Data Engineering, or Analytics.
• Strong proficiency in SQL and Python (pandas, scikit-learn, statsmodels).
• Hands-on experience with data governance, including data quality, metadata management, and stewardship.
• Experience with GenAI, LLMs, and AI agents.
• Experience with data pipelines using Airflow, dbt, or Spark.
• Familiarity with knowledge graph technologies like RDF and Neo4j.

Preferred Skills

• Experience with multi-agent frameworks (LangGraph, CrewAI, Claude SDK) and ontology design.
• Knowledge of DAMA-DMBOK or similar governance frameworks.

Key Skills

Education

Bachelor's degree