Enterprise Data Scientist & Analytics Lead (Remote)

mercor; San Francisco (CA); Hybrid; GBP 62,000 - 73,000; Part time

Job summary

Mercor is seeking an expert in data science and analytics to lead large-scale predictive modeling and governance for Fortune 500 clients. You will develop data science scenarios, ML workflows, and analytics pipelines across Snowflake, Databricks, Python/R, SQL, and BI platforms.

You will own end-to-end data products in production, drive rigorous methodologies including A/B testing, and contribute to enterprise data governance and privacy compliance.

Qualifications

• 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.

Responsibilities

• Construct enterprise data science scenarios for large-scale predictive modeling and multi-stakeholder analytics governance at Fortune 500 accounts.
• Build analytics tasks across ML model development, data pipelines, and business intelligence at scale.
• Develop data and MLOps scenarios using tools like Snowflake, Databricks, Python/R, SQL, Tableau/Power BI, and SageMaker/Vertex AI/MLflow.
• Apply enterprise data science methodologies, including statistical rigor, A/B testing frameworks, and MLOps best practices.
• Author rubrics that distinguish authentic enterprise data science judgment from generic textbook recall.

Skills

Data science

Analytics leadership

ML engineering

Enterprise data governance

Privacy compliance

Tools

Snowflake

Databricks

Python/R

SQL

Tableau/Power BI

SageMaker

Vertex AI

MLflow

Job description

Mercor is seeking an expert in data science and analytics to lead large-scale predictive modeling and governance for Fortune 500 clients. You will develop data science scenarios, ML workflows, and analytics pipelines across Snowflake, Databricks, Python/R, SQL, and BI platforms.

You will own end-to-end data products in production, drive rigorous methodologies including A/B testing, and contribute to enterprise data governance and privacy compliance.