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Enterprise Data Science Specialist

Role overview

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 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.

Key facts

Hard skills

About the company

Mercor logo

Mercor

  • Job Boards & Talent Marketplaces
  • 51–200
Our vast talent network trains frontier AI models in the same way teachers teach students: by sharing knowledge, experience, and context that can't be captured in code alone. Today, more than 30,000 experts in our network collectively earn over $2 million a day.

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Job description

About the job

Mercor connects elite creative and technical talent with leading AI research labs. Headquartered in San Francisco, our investors include Benchmark, General Catalyst, Peter Thiel, Adam D'Angelo, Larry Summers, and Jack Dorsey.

Position: Data Science and Analytics Experts
Type: Contract
Compensation: $60–$70/hour
Location: Remote

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.

Application Process (Takes 20–30 mins to complete)

  • Upload resume
  • AI interview based on your resume
  • Submit form

Resources & Support

  • For details about the interview process and platform information, please check: https://talent.docs.mercor.com/welcome
  • For any help or support, reach out to: support@mercor.com

PS: Our team reviews applications daily. Please complete your AI interview and application steps to be considered for this opportunity.

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