Data Scientist - Customer Understanding

Posted 9 Hours Ago
Be an Early Applicant
London, Greater London, England
Hybrid
Mid level
Fintech • Mobile • Payments • Software • Financial Services
Wise is one of the fastest growing Fintechs in the world and we’re on a mission to make money without borders a new norm
The Role
As a Data Scientist in the Marketing Team, you will develop predictive models to calculate Customer Lifetime Value (LTV), analyze customer behavior, and measure campaign effectiveness. Your work will support marketing strategies and resource allocation, helping to identify growth opportunities for Wise's services.
Summary Generated by Built In

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 life 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.

Job Description

Data Scientist - Marketing

We’re looking for a 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.
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.

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 you will 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 we do marketing

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 are familiar with lifetime value (LTV) modelling and econometrics/marketing mix modelling

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

  • 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 expert 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

  • You understand fundamental technologies such as Kafka and Docker, and don’t think twice about bringing up a new engine in docker-compose to have a play

  • 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 and pedantic 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.

Additional Information

Insight into life at Wise as an Analyst/Data Scientist

  • Inside the Wise Analytics Team

  • Analytics team career map

  • Analytics days at Wise

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.

Top Skills

Python
The Company
HQ: Austin, TX
6,000 Employees
Hybrid Workplace
Year Founded: 2011

What We Do

We’re making a positive, irreversible change in the world of finance. Together.

People on every continent around the world are choosing Wise to help them live, travel and work internationally. We’re the fairest, easiest way to send money overseas.

Built by and for people who live global lives, we make sending money abroad up to 8 times cheaper than the bank. This is money without borders - instant, convenient, transparent and eventually free.

For our customers, using Wise is as simple as sending money from A to B, but behind our app and website is a complex engine of currencies and routes, that’s being designed, built and powered by our talented teams in cities around the world.

We’re just at the beginning of our story and we’re growing at an incredible pace. We won’t stop until anyone, anywhere can send, spend and receive money wherever they are, whatever they’re doing. There’s still heaps to do and we can’t do it alone.

Why Work With Us

We are a mission-driven company, looking to change banking for the better. Current banking systems don’t let us send, spend or receive money across borders easily. Or quickly. Or cheaply. So, we’re building a new one. If you're looking for an autonomous work environment, where you'll face cool challenges, learn and grow, you'll like working at Wise

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WISE Offices

Hybrid Workspace

Employees engage in a combination of remote and on-site work.

Here at Wise we have a hybrid working model – a mix of working from home and from the office. Wisers can also work remotely for 90 days a year. By ‘remote’ we don’t just mean from home, but from wherever in the world you choose to!

Typical time on-site: 2 days a week
London, GB

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