Marketing Analytics Expert - AI Environments

Obsidian; Greater London; On-site; GBP 50,000 - 90,000; Full time

Job summary

Obsidian is building high-fidelity simulated work environments to evaluate and improve AI agents in real marketing work. You will help design the Marketing Analytics environments: briefs, artifacts, judgment criteria, and the planted issues a strong practitioner would resolve.

You will specify documents, dashboards, personas and tool states needed, write or review reference answers and criteria, and review AI agent attempts against a clear standard.

Qualifications

• Hands-on experience owning marketing analytics work, not just managing people.
• Fluent with GA4, Amplitude, Salesforce and ad platform reporting.
• Experience building AI training environments, RL environments or simulated case studies is strongly preferred.

Responsibilities

• Design task briefs drawn from your marketing analytics work, including the task tested, planted issue and 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 criteria that separate a strong response from a plausible but wrong one
• Review AI agent attempts and judge them against your own standard

Skills

Marketing analytics

Hands-on practitioner

Written reasoning

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

Applicants complete a short multiple-choice knowledge screener specific to this sub-domain before review.