Darum lohnt es sich
You’ll bring your expertise in applied data science, analytics engineering, experimentation, or ML-product work to build a high-fidelity environment that mirrors the tools, files, and cross-functional workflows of a modern enterprise data organization — and then author tasks grounded in the programs you actually run today.
Role Overview
Mercor is partnering with leading AI labs on Project Atlas — an initiative to build realistic enterprise environments that frontier AI agents are trained and evaluated in.
We're seeking experienced data-science and analytics professionals from Fortune 500 technology, financial-services, retail, and healthcare enterprises (e.g., Google, Meta, Netflix, Capital One, Amex, Walmart Labs, Target, UnitedHealth Group) to recreate the digital workspaces they run every day and design the tasks that genuinely challenge state-of-the-art AI.
Key Responsibilities
Build a realistic digital workspace centered on the Drive folders you use day-to-day — the design docs, experiment write-ups, stakeholder decks, SQL snippets, notebook exports, model cards, dashboards, and email threads that reflect how you actually organize your work — with some representation of the platforms that support it (e.g., Databricks / SAS Studio, Tableau / Power BI, Informatica PowerCenter / Talend)
Design multi-step tasks grounded in your real workflows that require navigating multiple apps, files, and stakeholders in a way that meaning
