Lead Data Scientist - Causal Inference

Salary: £66,000 - 106,000 per year

Requirements:

• An ability to simplify complex systems and ambiguous problems into clear hypotheses, useful abstractions and tractable analytical questions.
• Strong analytical judgement, with the ability to get to a useful answer quickly, refine it iteratively, and know when the evidence is sufficient to support a decision.
• Strong SQL and Python skills, with experience working with large, complex and imperfect datasets.
• Strong grounding in statistical analysis and causal inference, with experience designing both controlled experiments and observational studies.
• Experience applying machine learning, statistical modelling, NLP and LLM-based techniques to analyse customer behaviour and conversational data, diagnose root causes and identify the drivers of outcomes.
• Experience designing measurement frameworks for complex customer journeys and evaluating the impact of interventions.
• Strong product and business judgement, with a track record of using Data Science to influence important business decisions and drive measurable impact.
• Experience working on customer-facing products, ideally in customer support, customer operations or another high-volume service environment.
• Experience evaluating the impact of automation or AI-powered customer experiences.
• Experience applying predictive or behavioural modelling to support product or operational decision-making.
• Experience working with sensitive customer data in environments with strong security, privacy or compliance requirements.
• Experience combining quantitative analysis with qualitative or expert insight to solve complex problems.
• Familiarity with modern analytics and machine learning tooling in a cloud environment such as AWS.

Responsibilities:

• Build a clear, data-driven understanding of customer support quality across human and automated channels.
• Design metrics that reflect meaningful customer outcomes, including resolution quality, customer effort, process adherence, consistency, fairness, durability of resolution and cost effectiveness.
• Identify the root causes of issues by combining machine learning, statistical methods and domain expertise from colleagues to understand what genuinely drives customer outcomes.
• Turn analytical insight into concrete proposals to improve the customer experience, including product changes, process improvements, automation and better human support.
• Quantify the potential impact and value of opportunities to help the team prioritise where to invest.
• Design and analyse experiments to determine whether proposed changes genuinely improve customer and business outcomes.
• Use statistical modelling and causal inference where controlled experiments are not practical.
• Determine the right intervention for different customer problems — whether they should be automated, augmented by AI, handled by people or prevented altogether.
• Test and evaluate interventions to understand their impact on customer outcomes, operational effectiveness and cost.
• Shape the long-term automation capability roadmap, identifying what we should build next to maximise the value delivered over time.

Technologies:

• AI
• AWS
• Cloud
• Support
• LLM
• Machine Learning
• Python
• SQL
• Security
• Network

More:

We are Wise, a global technology company building the best way to move and manage the worlds money. We are on a mission to make international money movement easier, faster and cheaper for people and businesses everywhere. This full-time mid-senior Analyst role is part of our Customer Support team in London, working across London and Budapest. We believe in building money without borders, with teams that are diverse, equitable and inclusive, and we celebrate our international culture. We offer an environment where every Wiser feels respected, empowered to contribute and able to progress in their careers.

last updated 37 week of 2026