Senior Data Scientist - F500 Expert

Obsidian; Toronto; On-site; CAD 120,000 - 180,000; 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 and analytics contexts. The role focuses on scalable analytics governance, enterprise data pipelines, and model evaluation in high-stakes environments.

Ideal candidates have 5+ years of data science or ML engineering leadership within F500 settings, with a track record of owning enterprise data products and programs that require cross-functional

Qualifications

• 5+ years as a data scientist, analytics leader, or ML engineer in a Fortune 500 environment.
• Direct ownership of enterprise data products or analytics initiatives.
• Experience with governance, privacy compliance, and cross‑functional alignment.

Responsibilities

• Design enterprise data science scenarios for large-scale, high-stakes analytics.
• Draft reference outputs and rubrics reflecting senior F500 data leadership thinking.
• Develop and document data science methodologies, model docs, and executive insights.
• Collaborate across teams to ensure robust data pipelines and governance.

Skills

Data science

Analytics leadership

ML engineering

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.