Role Responsibilities
- Construct enterprise data science scenarios for large-scale predictive modeling and multi-stakeholder analytics governance at Fortune 500 accounts.
- Build analytics tasks across machine learning model development , enterprise data pipelines , and business intelligence at scale.
- Develop data and MLOps scenarios using tools like Snowflake , Databricks , Python/R , SQL , Tableau/Power BI , and enterprise ML platforms such as SageMaker , Vertex AI , and MLflow .
- Apply enterprise data science methodologies, including statistical rigor , A/B testing frameworks , and MLOps best practices to produce reference analyses and executive-level insights.
- Author rubrics that distinguish authentic enterprise data science judgment from generic textbook recall.
Qualifications
Must-Have
- 5+ years working as a data scientist, analytics leader, or ML engineer at a Fortune 500 technology or enterprise organization.
- Direct ownership of F500 data products , analytics initiatives , or machine learning systems in production.
- Fluency in enterprise data science tooling and methodologies, with an understanding of F500 data governance and privacy compliance.
Preferred
- Prior rubric, technical curriculum, or model documentation authorship.
Originally posted on Himalayas
