Growth Analyst

Hybrid, Manchester based - report to SVP Growth

About the Role

OrderYOYO builds the ordering apps and websites that thousands of restaurants across seven European markets use to take orders directly from their own customers. Our Growth team has one number to move: average orders per day per restaurant partner.

We're looking for a Growth Data Analyst to find where those orders are being lost, design the experiments that win them back, and prove it with data — across the end-user apps (iOS and Android), the restaurant partner websites, and the marketing stack.

This is a hands-on role. You'll write the SQL, build the test, read the result, and present it to the people who decide what ships next — working alongside a developer, a marketing manager, a paid media manager, and a data engineer.

Role Mission

Grow average orders per day per restaurant partner by finding where orders are lost across apps, websites and marketing channels, running the experiments that win them back, and making the Growth numbers trustworthy enough to decide on.

Core Responsibilities

• Own the end-user funnel view — from visit to order to repeat order — across apps and RP websites, by country and by restaurant partner.

• Run cohort, funnel, and retention analyses to find the biggest leaks in traffic, conversion, and repeat ordering, and size what fixing each one is worth in orders per day.

• Turn findings into a ranked backlog of hypotheses with expected impact and effort, and defend the ranking with the Growth team and Product.

• Design A/B tests end to end — hypothesis, success metric, guardrails, sample size and runtime, randomisation unit, and a pre-registered analysis plan — and set them up yourself on the apps and RP websites, working with the developer on feature flags or variant logic where code changes are needed.

• Check tests while they run (sample ratio, instrumentation, novelty effects) and read them out honestly, including when the result is flat or negative.

• Bring the same discipline to the marketing stack — paid media (Google Ads, Meta), email and push, SMS, landing pages, and restaurant partners' Google Business Profiles — using geo or restaurant-level splits and holdouts where a user-level test isn't possible, and judging traffic quality and incrementality on orders, not clicks.

• Own the definitions of the Growth metrics (AOD, conversion rate, new vs returning, retention), keep them consistent between GA4, the apps, and the warehouse, and chase tracking gaps with the data engineer and developer until fixes are verified with data.

• Partner with Algirdas on the Growth dashboards in Fabric and Power BI so reporting is automated rather than produced by hand.

• Build and own the experimentation playbook, and use AI as a daily tool — for SQL, analysis plans, and readouts — helping the team build small, repeatable AI workflows such as pre-test power calculations or weekly funnel checks. Experimentation is too important to be guesswork.

Must-Have Requirements

• 3 to 5 years in product, growth, or marketing analytics, ideally in a consumer app, marketplace, e-commerce, or food ordering business.

• Strong SQL — able to write and debug multi-step queries over event and transaction data without help.

• A track record of designing, running, and reading A/B tests, with the statistics to do it properly: power and sample size, significance, guardrail metrics, and the common ways a test lies (peeking, sample ratio mismatch, novelty).

• Technical enough to set up a test yourself: comfortable with feature flags or an experimentation tool, basic JavaScript or app event instrumentation, and reading a tracking plan.

• Hands-on with a product or web analytics stack (GA4 or similar) and a BI tool (Power BI, Looker, Tableau, or similar).

• Comfortable testing in marketing channels as well as in product: campaign experiments in Google Ads or Meta, email or push tests, and geo or holdout designs for measuring incrementality.

• Uses AI tools daily for analysis work and can show how it changed the way you work.

• Clear, confident communication — able to take a messy result and explain to a non-technical audience what it means and what to do next, in writing and in person.

• Owns outcomes, not tasks, and is comfortable setting the plan in a small team rather than waiting for one.

• Fluent English. Danish is not required.

Strong-to-Have Experience

• Python or R for statistical analysis and automating recurring checks.

• Microsoft Fabric, Power BI, or another lakehouse and BI setup.

• Mobile app experimentation (Firebase, Optimizely, GrowthBook, Statsig, or similar) and web experimentation on multi-tenant or white-label sites.

• Sequential or Bayesian test methods, or quasi-experiments where a true A/B test isn't possible (for example, market-level or restaurant-level rollouts).

• Paid media data (Google Ads, Meta) and attribution, to judge traffic quality as well as conversion.

• A customer data platform and B2C engagement tooling (Segment, Braze, Firebase messaging, or similar), including running lifecycle tests in them.

• Building AI-assisted workflows or agents for analysis, not only using chat tools.

Who We Are

At OrderYOYO, company culture comes first. We create a positive, inclusive environment where people are trusted to do their best work and take ownership of what they build. Personal development is central to how we work — engineers are encouraged to grow technically, take responsibility, and help shape how our products and platforms evolve.

We help restaurants succeed online by providing branded websites, mobile apps, and tailored marketing solutions, giving them full control of their business. By removing high commission fees charged by third-party platforms, we empower restaurants to grow sustainably.

Through our partnership with AppSmart, the market leader in POS and in-store systems, we've become the largest restaurant-focused platform in Europe.

What We Offer

• A salary of 80,000/ annually

• A hybrid role based in Manchester.

• High ownership and autonomy over the analysis and experiments you run.

• The opportunity to directly move a revenue-critical metric: orders per day.

• A strong focus on data quality, honest experimentation, and analytics best practices.

• A collaborative, international Growth team.

• Real emphasis on learning, mentoring, and personal development.