Senior Data Scientist - Marketing

Location: Global

Team: General

About the Role

Wise is a global technology company revolutionizing how people and businesses move and manage money across borders with minimal fees and maximum ease. As a Senior Data Scientist in our Marketing Team, you'll drive growth by developing advanced models like Customer Lifetime Value (LTV), causal inference for campaign impact, and Marketing Mix Models (MMM) to identify high-impact opportunities and optimize resource allocation. You'll model customer behaviors to target the right audiences and collaborate with data analysts and marketers to turn insights into action, directly contributing to Wise's mission of money without borders. Work autonomously in a diverse, international team in London (Global role), partnering with Organic and Paid Acquisition groups to help millions discover Wise. Your days will involve building and maintaining models, evaluating new ideas, and communicating data-driven recommendations that shape marketing strategies. Enjoy the freedom to define your vision, gather feedback from curious peers, and make high-impact decisions in a flexible, inclusive environment. We're seeking passionate, data-driven experts who thrive on ownership and precision. Qualifications matter less than your experience and ability to articulate impact—especially if you're from an underrepresented background. Join us to build better products, live our values, and empower every Wiser to progress.

Key Responsibilities

• Develop predictive models to calculate Customer Lifetime Value (LTV) for prioritizing marketing efforts
• Model customer behaviour data and product usage to identify target audiences
• Use causal models to measure incremental effects of CRM and Invite campaigns
• Apply causal inference to decide campaign delivery to users
• Build and maintain Marketing Mix Models (MMM) to guide growth investments
• Collaborate with Data Analysts to help them use LTV and MMM models
• Build new models, evaluate ideas, and communicate insights on marketing strategies
• Partner closely with Organic and Paid Acquisition marketing teams

Required Qualifications

• Familiar with lifetime value (LTV) modelling and econometrics/marketing mix modelling
• Experience with Bayesian approaches to machine learning, and using neural networks (ideally PyTorch)
• Good understanding of statistics, particularly Bayesian reasoning, and ability to estimate result accuracy
• Good understanding of causal inference concepts and experience with ML models for causal inference
• Solid knowledge of Python, ability to make and justify design decisions in code
• Experience using external data pulled via APIs
• Understanding of fundamental technologies such as Kafka and Docker
• Ability to take ownership of a project from end to end
• Data-driven with a structural and pedantic approach, strong prioritization and time management
• Comfortable visualising and communicating data to various audiences

Preferred Qualifications

• Experience building REST services or UIs in Python
• Familiarity with a range of model types (gradient boosting, neural networks, linear regression)
• Experience in diverse, international teams

Required Skills

• Lifetime value (LTV) modelling
• Econometrics and marketing mix modelling
• Bayesian machine learning
• Neural networks (PyTorch)
• Statistics and Bayesian reasoning
• Causal inference
• Python programming
• API data integration
• Kafka and Docker
• Data visualization and communication

Benefits

• RSUs (stock options)
• Flexible working
• Parental leave
• Learning budget
• Paid sabbatical after 4 years
• Health insurance
• Company retreat
• Wise card

Wise is an equal opportunity employer committed to building a diverse workforce.