Data Steward/ Scientist

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) Strong proficiency in SQL and Python (e.g., pandas, scikit-learn, statsmodels, or similar) Have familiarity with designing, developing and deploying statistical models, machine learning algorithms, and analytical framework to support channel business decisions. 2+ years of experience in a retail or consumer goods environment Practical experience building or deploying AI agents or LLM-powered applications Experience with data governance practices, including data quality, metadata management, or data stewardship Familiarity with knowledge graph technologies (RDF, property graphs, Neo4j)