Data Science & Analytics Expert

aitrainer; Deutschland; Vor Ort; EUR 75.000 - 95.000; Vollzeit

Zusammenfassung

Aitrainer is seeking experienced data-science professionals to partner with leading AI labs on Project Atlas. This role involves building realistic digital workspaces and designing tasks that challenge state-of-the-art AI.

Ideal candidates have a quantitative degree and 3+ years of experience in data science, analytics engineering, or ML product work.

Join us to contribute to pioneering AI research and benchmarking while collaborating with top companies.

Qualifikationen

• 3+ years of full-time experience at a Fortune 500 technology, financial-services, retail, or healthcare enterprise.
• Strong analytical thinking and writing skills to translate workflows into task specs.

Aufgaben

• Build a realistic digital workspace reflecting your day-to-day tools and organization.
• Design multi-step tasks grounded in real workflows that challenge AI agents.
• Collaborate with data-science experts to shape task designs and evaluation criteria.
• Contribute to AI research and benchmarking.

Kenntnisse

Applied data science

Analytics engineering

Experimentation

ML engineering

Strong analytical thinking

Ausbildung

BS / MS / PhD in a quantitative discipline

Tools

Databricks

SAS Studio

Tableau

Power BI

Informatica PowerCenter

Talend

Jobbeschreibung

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.

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.

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 meaningfully challenges frontier AI agents

Collaborate with other data-science and analytics experts in your field to design the environment, shape task scope, and review each other's scenarios for realism and rigor

Work asynchronously with research teams to refine task designs and evaluation criteria for data-science agent benchmarks

Contribute to frontier AI research and benchmarking — the work you produce directly informs how leading labs train and evaluate the next generation of AI systems

Ideal Qualifications

BS / MS / PhD in a quantitative discipline

3+ years of full-time experience at a Fortune 500 technology, financial-services, retail, or healthcare enterprise

Background in one or more areas such as:

• Applied data science (forecasting, causal inference, ML modeling)
• Analytics engineering / data modeling
• Experimentation / A-B testing platforms and methodology
• Product analytics and business-insights work
• ML engineering or decision-science / operations-research
• Day-to-day use of Databricks / SAS Studio, Tableau / Power BI, and Informatica PowerCenter / Talend

Strong analytical thinking and writing — able to translate data-science workflows into structured task specs

Compensation Note

This project is expected to begin on an effective hourly rate, but will transition to a model where experts are compensated based on throughput of quality work rather than a flat accruing hourly rate.

About Mercor

Mercor is a talent marketplace that connects top experts with leading AI labs and research organizations. Backed by investors including Benchmark, General Catalyst, Adam D'Angelo, and Jack Dorsey. Thousands of professionals across domains contribute to projects shaping the next generation of AI systems.

We consider all qualified applicants without regard to legally protected characteristics and provide reasonable accommodations upon request.