Senior 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.

If you’re the kind of person who loves to sit in the sweet spot of harnessing the power of data and technology, performing rigorous scientific insight and having a direct strategic impact on the product - this is the role for you.

Our Mission

We are on a journey to become a truly product-first organisation. Having built a world-class infrastructure, we are now focused on creating a deeply integrated ecosystem where our products are the primary drivers of customer value and business growth.

As a Senior Data Scientist, you will be at the heart of this transition. You will be architecting the economic lens through which we view our future. By untangling the complex relationship between product engagement and commercial health, you will provide the evidence needed to align our strategic direction with our product innovation.

The Role

We’re looking for a strategic lead to bridge the space between complex causal inference and long-term business goals. This role is built for an analytical partner who enjoys navigating the nuance of commercial data—exploring how product engagement translates into lasting customer relationships.

You will be instrumental in defining the economics of our products, providing the clarity required to shift our focus from simple acquisition to high-value expansion. By shaping the frameworks that help us prioritise our efforts and defining what success looks like across the entire customer journey, you will ensure our growth is both sustainable and product-led.

What You’ll Do You will own the "How" and the "Why" behind our causal modelling, taking projects from initial ideation through to production and strategic influence.

• Causal Retention Modelling: Lead the development of causal models to untangle the relationship between product engagement and long-term customer retention. You will move beyond simple correlation to quantify the "stickiness" of specific features, providing a definitive roadmap for which behaviours act as the strongest deterrents against churn.
• Lifecycle Value (LTV) Architecture: Design and implement a comprehensive "Expansion LTV" framework. You will combine churn-reduction data and revenue estimates to create a product-level value calculation that guides our investment guardrails and prioritisation.
• Portfolio Health & Forecasting: Formulate high-fidelity, bottom-up revenue models that account for customer eligibility, conversion funnels, and seasonal trends. You will provide the predictability needed to ensure the business meets its long-term commercial objectives.
• Scientific Rigour & Methodology: Implement best-in-class methodologies to ensure our strategic decisions are based on statistical truth rather than noise.
• Uplift Data Science Culture and Evangelise Best Practices: Act as a lead influencer for our data community. You will champion the transition from descriptive analytics to predictive and causal modelling, ensuring our strategic decisions are based on scientific truth. Own the standards for version control, code quality (Python/SQL), and reproducible research. You’ll ensure our technical debt remains low and our methodology remains high.
• Mentorship & Coaching: Take an active role in developing the next generation of analysts and data scientists. You will provide technical guidance, conduct rigorous peer reviews, and foster a culture of continuous learning and curiosity.
• Stakeholder Influence: Act as a strategic partner to General Managers and Product leads. You will translate complex technical findings into actionable commercial recommendations that drive the bottom line.

What You’ll Bring

• Technical Excellence: Expert-level proficiency in Python and SQL. You are comfortable building and deploying models within a modern data stack (BigQuery/Snowflake, dbt, Git).
• Methodological Depth: Extensive experience in Causal Inference, Time-Series Forecasting, and Advanced Statistics. You know how to prove "lift" and "value" in complex, multi-variable environments.
• Commercial Acumen: You think in terms of unit economics—LTV, CAC, and Payback cycles. You have a track record of connecting data science initiatives to tangible business P&L impact.
• Experience: 5+ years in a Data Science role, preferably within a high-growth fintech, SaaS, or revenue-driven environment.
• Ownership Mindset: You are a proactive self-starter. You don't wait for a ticket; you spot the "value gap" in the business and build the model to fill it.
• Communication Mastery: You can explain a Bayesian forecast to a developer and then explain the "so what" to a CEO with equal clarity and impact.