Lead Data Scientist - Causal Inference

Responsibilities

• 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.
• Shape the long-term automation capability roadmap, identifying what we should build next to maximise the value delivered over time.

Requirements

• Strong SQL and Python skills, with experience working with large, complex and imperfect datasets.

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.

Preferred

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.

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 .

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 .