Senior Data Scientist - F500 Expert

Mercor; Toronto; On-site; CAD 110,000 - 170,000; Full time

Job summary

Mercor seeks senior data science and analytics professionals to design evaluation tasks for AI systems operating in Fortune 500 enterprise data contexts. The role involves crafting enterprise data science scenarios, reference outputs, and rubrics that capture how senior F500 data leaders think.

Responsibilities include constructing large-scale analytics tasks, building analytics workflows across ML model development and data infrastructure decisions, and applying rigorous enterprise data science

Qualifications

• 5+ years as a data scientist, analytics leader, or ML engineer in a Fortune 500 tech or enterprise setting.
• Ownership of F500 data products, analytics initiatives, or production ML systems.
• Fluency with enterprise data science tooling and governance, privacy, and cross-functional alignment.

Responsibilities

• Construct enterprise data science scenarios across large-scale modeling and analytics governance.
• Develop tasks for ML model development, data pipelines, BI at scale, experimentation, and data strategy.
• Draft reference outputs, rubrics, and executive-level insights from analyses.
• Create rubrics that differentiate authentic enterprise data science judgment from rote recall.

Skills

Data science leadership

Fortune 500 experience

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.