Data Scientist

We’re reinventing payments. In less than four years, Dojo disrupted the market to become the largest and most loved acquirer in the UK. Our payments infrastructure, purpose-built for in-person commerce, is game changing.

Now, over 150,000 customers across four countries choose to transact billions with us every year. But we’re just getting started.

Our people are the driving force behind our success. They are our greatest investment and our ultimate competitive advantage. We hire exceptional people and give them the autonomy, trust, and ownership to thrive. The results take care of themselves.

The role

Dojo is empowering the experience economy, and data sits at the very centre of our ambition. As an Economist, you'll identify the true causal impact of our actions, from pricing shifts to product launches. You're the person we turn to when causal questions get tough and clean data is scarce. This is a specialist, depth-first role where you'll protect research integrity, challenge tempting correlations, and ensure our strategic decisions stand up to scrutiny.

What you will do...

• Frame the problem & own the scope: Reframe ambiguous requests around key business decisions, proactively tying econometric work to revenue, cost, or churn levers.
• Design advanced experiments: Run proper A/B tests and design sophisticated studies like synthetic controls or staggered rollouts when clean randomization is scarce.
• Apply rigorous modeling: Build reduced-form and simple structural models, utilizing strong theoretical grounding to adapt textbook methods to real-world challenges.
• Build robust metrics: Architect metrics and metric trees that resist misinterpretation, writing production-quality SQL and Python to shape data at scale.
• Communicate honestly: Translate complex causal findings and statistical uncertainty into narrative-driven insights that guide non-technical decision-makers.
• Lead with AI fluency: Use AI tools to accelerate code and analysis while maintaining critical judgment and catching theoretical reasoning errors.

What you will bring...

• Expertise in causal inference: Deep command of econometric methods including instrumental variables, RDD, DiD, and fixed-effects.
• Strong theoretical foundation: Ability to reason from first principles when standard textbook methods do not fit.
• Fluent programming skills: Proficiency in statistical programming with Python and SQL for sourcing and shaping data at scale.
• Intellectual honesty: Commitment to quantifying uncertainty, stating assumptions, and protecting research integrity under pressure.
• Clear communication: Ability to translate complex causal findings into simple, compelling narratives for non