Senior Data Scientist - F500 Expert

Obsidian; New York (NY); On-site; USD 140,000 - 210,000; Full time

Job summary

Mercor is seeking senior data science and analytics professionals to build evaluation tasks for AI systems operating in Fortune 500 enterprise data contexts. You will craft enterprise data science scenarios, draft reference outputs, and write rubrics that capture senior leaders' thinking.

Ideal candidates have 5+ years in data science or ML engineering within large organizations, with direct ownership of enterprise data products or ML systems in production.

Qualifications

• 5+ years working as a data scientist, analytics leader, or ML engineer in large-scale environments.
• Experience owning data products or ML systems in production within enterprise contexts.
• Strong grasp of enterprise data governance, privacy compliance, and cross-functional alignment.

Responsibilities

• Design enterprise data science scenarios for Fortune 500 engagements across analytics governance and data infrastructure decisions.
• Develop tasks across ML model development, pipelines, BI at scale, experimentation, and data strategy.
• Document rubric, reference analyses, and executive-level insights to distinguish authentic data science judgment.

Skills

Senior data scientist

Analytics leadership

ML engineer

Tools

Snowflake

Databricks

Python/R

SQL

Tableau

Power BI

SageMaker

Vertex AI

MLflow

Job description

Role Overview

• Mercor is seeking senior data science and analytics professionals to build evaluation tasks for AI systems operating in Fortune 500 enterprise data and analytics contexts.

• The workflows are calibrated to the data scale, model complexity, and business-critical stakes of Fortune 500 and large public company data operations.

• Contributors design enterprise data science scenarios, draft reference outputs, and write rubrics that capture how senior F500 data leaders think.

Key Responsibilities

• Construct enterprise data science scenarios spanning large-scale predictive modeling, multi-stakeholder analytics governance, and complex data infrastructure decisions at F500 accounts.

• Build analytics tasks across F500 machine learning model development, enterprise data pipelines, business intelligence at scale, experimentation/causal inference, and data strategy.

• Develop data and MLOps scenarios involving tools such as Snowflake, Databricks, Python/R, SQL, Tableau/Power BI, and enterprise ML platforms (SageMaker, Vertex AI, MLflow) in F500 stacks.

• Apply enterprise data science methodologies (statistical rigor, A/B testing frameworks, model validation, MLOps best practices) and produce reference analyses, model documentation, and executive-level insights.

• Author rubrics that distinguish authentic enterprise data science judgment from generic textbook or tutorial-level recall.

Ideal Qualifications

• 5+ years working as a data scientist, analytics leader, or ML engineer at a Fortune 500 technology or enterprise organization (Google, Meta, Amazon, Microsoft, Netflix) or inside an F500 data/analytics organization (JPMorgan, UPS, Unilever, PepsiCo, Walmart).

• Direct ownership of F500 data products, F500 analytics initiatives, or F500 machine learning systems in production.

• Fluency in enterprise data science tooling and methodologies, plus understanding of how F500 data governance, privacy compliance, and cross-functional stakeholder alignment actually work.

• Prior rubric, technical curriculum, or model documentation authorship is a plus.