Data Scientist — Customer Understanding

Data Scientist/Senior Data Scientist - Customer Understanding

We’re looking for Data Scientists to join our growing Marketing and Product Teams in London. This role is a unique opportunity to have an impact on Wise’s mission, grow as a Data Scientist (developing cutting-edge techniques) and help save our customers money.

Your mission: 

Wise has already pioneered new ways for people to transfer money across borders and currencies. Our customers can also manage their hard-earned money with the world’s first platform to offer true multi-currency banking. Your mission is to help make people aware of Wise as a solution for cross-border money needs, and help us target our offering to better serve existing customers.

Here’s how you’ll be contributing to Marketing and Product

• You will help the Marketing and Product tribes find the biggest growth opportunities by measuring the incremental effect that marketing campaigns and product changes have on business metrics
• You will use causal inference to decide which campaigns and features should be delivered to each user. You will help own and develop our groundbreaking open-source framework for automatic causal model selection (auto-causality)
• You will model customer behaviour data and product usage so we understand which audiences to target and how (LTV/churn modelling, neural-lifetimes package)
• You will understand the varying needs and responses of different groups of our customers (Customer Segmentation, in particular using state of the art causal inference models)
• You will work closely with Data Analysts and you will help them understand and use models that you build (Causal Inference, LTV,  and Customer Segmentation models)

A bit about you: 

• You have a good understanding of causal inference concepts and have some experience with machine learning models for causal inference.
• You are familiar with lifetime value (LTV) modelling and customer segmentation
• You have experience with Bayesian approaches to machine learning, as well as with using neural networks, ideally PyTorch
• You have a good understanding of statistics, in particular Bayesian reasoning, and can estimate how accurate your results are, but also know when to stop analysing and deliver results
• You are familiar with a range of model types, and know when and why  to use gradient boosting, neural networks, good old linear regression, or a blend of these
• You have a solid knowledge of Python, and are able to make and justify design decisions in your Python code; you can throw together a REST service or a UI if need be. You’ve used external data pulled via APIs before

We’re people without borders — without judgement or prejudice, too. We want to work with the best people, no matter their background. So if you’re passionate about learning new things and keen to join our mission, you’ll fit right in.

Also, qualifications aren’t that important to us. If you’ve got great experience, and you’re great at articulating your thinking, we’d like to hear from you.

And because we believe that diverse teams build better products, we’d especially love to hear from you if you’re from an under-represented demographic.

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