What are the responsibilities and job description for the Senior Data Scientist - Marketing position at Wise?

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

We’re looking for a Senior Data Scientist to join our growing Marketing Team in London. This role is a unique opportunity to have an impact on Wise’s mission , grow as a Data Scientist and help save people money.

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.

Here’s how you’ll be contributing to Marketing;

You will help the Marketing tribe find the biggest opportunities for growth.
You will do this by developing predictive models to calculate Customer Lifetime Value (LTV), aiding in the prioritization of marketing efforts and resource allocation.
You will model customer behaviour data and product usage so we understand which audiences to target and how.
You will also use causal models to measure the incremental effect that CRM and Invite campaigns have on business metrics. You will use causal inference to decide which campaigns should be delivered to each user.
You will help us understand in what growth activity to invest (Marketing Mix Models).
You will work closely with Data Analysts and help them understand and use models that you build (LTV or MMM models).
Your average day will include building new models, maintaining models used by everyone in the marketing tribe, evaluating new ideas and communicating what models can tell us about how and why we grow.

This role will give you the opportunity to :

Have a direct impact - You will closely partner with every marketing team within both Organic and Paid Acquisition and help millions of people and businesses to learn about how Wise can help them.

Work autonomously - we believe people are most empowered when they can act autonomously. So rather than telling you what to do, you’ll work with your team to create a vision of your own. Of course, you can always gather feedback from smart, curious people across Wise but you’ll have the freedom to make your own calls.

Be part of a diverse team - You will work in a team of Data scientists, Analysts and Marketeers.

Be part of our mission to make money without borders the new normal.

Qualifications

About you :

You have expert knowledge of Python, and are able to make and justify design decisions in your Python code.

You have experience in building lifetime value (LTV) and Marketing Mix Modelling (MMM) models.

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 good understanding of statistics, in particular Bayesian reasoning.

You are able to take ownership of a project and see it through from end to end, with past experience in doing so.

You are data-driven with a structural approach. You need to be able to prioritise the value you can add, and manage your time effectively.

You see a bigger picture of business processes and can cut through vagueness to define precisely where and how a model would fit into our stack and what value it would add.

You are comfortable with visualising and communicating data to various audiences, you easily articulate and present your ideas.

Some extra skills that are great (but not essential) :

You have a good understanding of causal inference concepts and have some experience with machine learning models for causal inference.

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 .

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