Omniscient is an organic growth agency that builds revenue-focused organic growth systems for B2B software companies — optimized for both search engines and generative AI.

We pride ourselves on being lean, agile, and experimental. Our team thrives on R&D and innovation, always exploring the smartest ways to deliver exceptional results. We believe in a culture of building and shipping — whether it’s client deliverables, new services, or internal tools that keep us ahead of the game.

If you’re looking for a role where you’ll tackle challenging problems, work with ambitious brands, and help shape the future of organic growth, let’s talk.

Learn about the principles that drive how we work and build a company.

About this role

Our clients invest heavily in SEO, AI search, content, and organic growth.

They have dashboards, analytics platforms, and plenty of performance data. But the questions that matter most are often harder to answer:

What's actually driving our organic growth (and where are we underperforming)?

Why are certain metrics improving while pipeline remains flat?

How do we know whether an initiative is working?

Do we have the data (tracking, integrations, tooling) to make the right decisions?

What should we do differently based on what we're learning?

Your job is to help us answer those questions.

You'll be our first dedicated marketing analytics hire, working across client engagements to improve measurement, develop meaningful insights, and connect organic growth performance to business outcomes.

This is a senior, hands-on analytical leadership role. You'll work directly with clients and our organic growth strategists, diagnose measurement challenges, build reports and analyses that guide decisions, and help develop repeatable approaches that raise the analytical capabilities of our entire team.

We're not looking for a full-time analytics engineer or data scientist. We need someone who understands marketing, knows how to work with imperfect data, asks great questions, and can translate complexity into clear recommendations for business stakeholders.

AI search measurement is a particularly exciting part of the opportunity. Many of the traditional ways of measuring organic marketing are becoming less useful, and we want someone who can help us develop credible, practical approaches to evaluating this emerging channel.

You'll support our team’s experiments, some of them conventional CRO tests and some of them brand new – like measuring whether adding FAQ content to a landing page moves citation share in LLM results.

We're a fully remote team. We require work hours to overlap +/- 3 hours with US Eastern Time, since you'll be working directly with US-based client stakeholders.

Your responsibilities

Turn business questions into actionable insights. Work with clients and internal stakeholders to clarify what they're trying to understand, determine which data can answer their questions, analyze the evidence, and recommend what to do next.

Connect marketing performance to business outcomes. Analyze organic search, AI visibility, website behavior, conversions, CRM data, and other marketing signals to understand how our work contributes to qualified leads, pipeline, and revenue. Understand the strengths and limitations of different attribution approaches.

Elevate client reporting. Develop clear, insightful reporting that goes beyond rankings, traffic, and channel metrics. Help our clients understand what's happening, why it matters, and what decisions they should make. Present findings confidently to marketing leaders and executives.

Diagnose measurement gaps. Audit existing analytics setups, identify tracking problems, evaluate data quality, and determine which issues materially affect business decisions. Work with client-side analysts, developers, and other technical stakeholders to scope and prioritize necessary fixes.

Support measurement and experimentation. Help our strategists evaluate whether new initiatives are working, from conversion improvements to AI search optimization. Develop practical hypotheses, measurement plans, and approaches to interpreting results, recognizing when conclusions are uncertain or causal impact cannot be established.