Data Steward/ Scientist

Role: Data Steward/ Scientist       
Mode: Onsite
Duration: Full-time
Visas: USC/EAD EAD
Relocation: Acceptable
Location: Cupertino, CA

Job Description:
We are looking for a rare blend of analytical depth, data ownership mindset, and modern AI fluency. As a senior data steward & scientist you will sit at the intersection of advance analytics, knowledge representation, data governance and intelligent automation - helping us unlock the full value of our data assets whole ensuring data is trusted, well understood and for purpose.
You will not just analyze data - you will govern the definitions that describe it, and deploy AI agents that automate decision on top of it.

Key Responsibilities:
Data Science & Analytics:

• Have familiarity with designing, developing and deploying statistical models, machine learning algorithms, and analytical framework to support channel business decisions
• Have hands on experience in conducting exploratory data analysis to surface insights on sales performance, inventory
• Have familiarity with building an maintaining forecasting models
• Translate complex analytical outputs in clear, actionable recommendations for business audience

Data Governance & Metric Definition:

• Serve as the data steward for key data domains owning definitions, lineage and quality standards
• Develop an maintain data dictionaries, business glossaries and lineage documentation
• Define and monitor data quality riles, triage and resolve data issues in partnership with engineering
• Ensure AI outputs and agent generated content are traceable back to governed, trusted data sources
• Design, build and deploy AI agents that automate recurring analytical workflow in data governance

What You’ll bring
Required-

• 5+ years of experience across data science, data engineering, or analytics — with at least 2 years in a retail or consumer goods environment
• Strong proficiency in SQL and Python (pandas, scikit-learn, statsmodels, or similar)
• Familiarity with causal inference methods and experiment design
• Familiarity with building and maintaining data pipelines (Airflow, dbt, Spark, or similar)
• Practical experience building or deploying AI agents or LLM-powered applications
• Familiarity with knowledge graph technologies (RDF, property graphs, Neo4j)
• Experience with data governance practices — data quality, metadata management, or data stewardship
• Ability to communicate complex findings clearly to non-technical stakeholders

Nice to have:

• Experience with multi-agent frameworks (Claude Agent SDK, LangGraph, CrewAI, or similar)
• Exposure to ontology design or entity resolution in a retail context
• Familiarity with data governance frameworks (DAMA-DMBOK or simila
• Graph query languages (SPARQL, Cypher)
• Cloud data platform experience (Snowflake, BigQuery, Databricks)