Lead Data Scientist - Causal Inference

Company Description

Wise is a global technology company, building the best way to move and manage the world's money.

Min fees. Max ease. Full speed.

• Whether people and businesses are sending money to another country, spending abroad, or making and receiving international payments, Wise is on a mission to make their lives easier and save them money.
• As part of our team, you will be helping us create an entirely new network for the world's money.
• For everyone, everywhere.
• More about our mission and what we offer .

Job Description

About the role

• We're looking for an experienced Data Scientist to join our Customer Support team in London, working as part of a team based across London and Budapest.
• You'll help us understand how well our customer support experience is working, identify the biggest opportunities for improvement, and shape the path towards greater automation.
• This is an analytical Data Science role with a strong product focus.
• You'll use customer, conversational and operational data to measure service quality, diagnose issues, propose solutions and evaluate whether they improve outcomes.
• A key part of the role is simplifying complex customer journeys and operational systems into clear, tractable problems the team can act on.
• You'll work closely with Product, Design, Operations and Engineering to build a shared understanding of how the system works and turn insight into action.no

What you'll do

Measure and diagnose

• 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.

Identify and test solutions

• 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.

Shape the automation strategy

• 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.

What we're looking for

Essential

• 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 (e.g., classical ANOVA, non-parametric uncertainty quantification, Bayesian estimation) 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.

Preferred

• 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.

What success looks like

• Success in this role means making a complex customer support system understandable enough that the team can make better decisions about it.
• You'll create clear ways of thinking about customer support quality, identify the biggest opportunities to improve outcomes, and turn those insights into concrete interventions that can be tested and measured.
• Over time, you'll help us make better decisions about where to automate, where to invest in human support, and which new capabilities to build — creating a support model that delivers more value to customers while becoming increasingly effective and scalable.

Additional Information

For everyone, everywhere. We're people building money without borders — without judgement or prejudice, too. We believe teams are strongest when they are diverse, equitable and inclusive.

• We're proud to have a truly international team, and we celebrate our differences.
• Inclusive teams help us live our values and make sure every Wiser feels respected, empowered to contribute towards our mission and able to progress in their careers.
• If you want to find out more about what it's like to work at Wise visit Wise.Jobs .
• Keep up to date with life at Wise by following us on LinkedIn and Instagram .