Marketing Analytics Expert - AI Environments

Mercor

Toronto

On-site

CAD 70,000 - 100,000

Full time

4 days ago
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Job summary

Mercor is seeking a Marketing Analytics designer to craft training environments that mimic real marketing workflows. You will shape briefs, artifacts, and judgment criteria to stress test AI agents, ensuring the tasks mirror actual marketing analytics challenges in a Toronto-area context.

You will operate across analytics tools like GA4, Amplitude, and Salesforce, and you will articulate complex decisions with precise written reasoning for evaluation and iteration.

Qualifications

  • Hands-on practitioner experience in marketing analytics.
  • Ability to articulate decisions with clear written reasoning.
  • Experience designing realistic analytics training environments.

Responsibilities

  • Design task briefs drawn from work you have actually done in marketing analytics, including what the task is really testing — the planted issue and the decision a strong practitioner should reach
  • Specify the documents, dashboards, personas and tool states a realistic version of that task requires
  • Write or review the reference answer and the criteria that separate a strong response from a plausible-but-wrong one
  • Review AI agent attempts and judge them against your own standard

Skills

Hands-on marketing analytics
Clear written reasoning
Environment design thinking

Tools

Google Analytics 4
Amplitude
Salesforce
Ad platform reporting

Job description

About the work

We are building high-fidelity simulated work environments used to evaluate and improve AI agents on real marketing work. Each environment reproduces a marketing org's actual tool surface — email, storage, CRM, project management, social media management, web analytics, AEO/SEO, ads, CMS, product analytics and support — populated with realistic documents, dashboards, personas and deliberately planted problems.

You will help design and pressure-test the Marketing Analytics environments: the briefs, the artifacts, the judgment calls a strong practitioner would make, and the errors a weaker one would miss.

What you will do
  • Design task briefs drawn from work you have actually done in marketing analytics, including what the task is really testing — the planted issue and the decision a strong practitioner should reach
  • Specify the documents, dashboards, personas and tool states a realistic version of that task requires
  • Write or review the reference answer and the criteria that separate a strong response from a plausible-but-wrong one
  • Review AI agent attempts and judge them against your own standard

Tasks span the capabilities we measure: diagnosing what happened from messy or conflicting data, prioritizing and making tradeoffs, planning and executing, QA and reconciliation, triage and escalation, research and evaluation, reporting, and orchestrating multi-step work across several tools.

Marketing Analytics scope

Anomaly detection, channel-performance synthesis, cross-source reconciliation, attribution and incrementality reading, and reporting that supports an actual decision.

Who we are looking for
  • Hands-on practitioner experience in marketing analytics — you have owned this work, not only managed people who do it
  • Fluent in the tools of the domain: Google Analytics 4, a product analytics tool such as Amplitude, a CRM such as Salesforce, and ad platform reporting
  • Prior experience building AI training environments, RL environments or simulated case studies is strongly preferred
  • Rubric Academy or Rubric Bootcamp certification is strongly preferred
  • Clear written reasoning — much of the value is in explaining why a decision is right
Screening

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