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.
We’re on a mission: to make money without borders the new norm. We’ve got 11 million customers across the globe and we’re growing. Fast.
We’re creating a scalable, high performing platform for our customers. And we need Data Science Interns to join us in our mission. This is a paid internship that will run throughout the summer.
At Wise you’ll work on challenging technical problems across the full product life-cycle and you’ll help us gain the understanding necessary to give our customers a great experience.
How you’ll contribute to our team of data scientists:
You’ll work on a real data science project that matters to us, using up-to-date machine learning techniques. We can’t say what project yet, but your internship will be centred around this.
You will help analysing data that will help us prioritise the most customer significant changes in the product
Participate in building the most advanced machine learning based solutions to help us scale
Help take Wise to the next level as we scale to impact 100’s of millions more customers
This role will give you the opportunity to:
Learn and develop professionally. You’ll work closely with your Wise team. You’ll learn by doing. And you’ll be guided and supported along the way
Understand the Wise way through lots of opportunities to learn about our business and how it works
Broaden your network. There are a LOT of experienced people here at Wise who are keen to share their experience and knowledge with you. They’ll want to learn from you and get your perspective on things too
Choose your path to impact. We believe people do great things when they can act autonomously. So, instead of being told what to do, you’ll work with your team to create a vision of your own. You can always gather feedback from smart, curious people across Wise, but you’ll have the freedom to make your own calls
Be flexible in how and where you work. We understand everyone needs a little something different - so we’ll do our best to make it happen
Inspire teams with your ideas, knowledge and self-starting attitude
What does it take? These things are a must:
You are a student studying a Bachelors, Masters, or PhD degree. This might be in Computer Science, Mathematics, Engineering or any other STEM subject
You are able to start a full time graduate job in September 2023
Knowledge of computer science and machine learning fundamentals including data structures, algorithms, data analysis, linear algebra and statistics
Understanding principles of machine learning
You should have a good command of Python 3 and be familiar with major data analysis and ML frameworks
A self-started side project(s) that you are proud to talk about
Great communication skills and the ability to articulate complex, technical concepts to a non-technical audience
Curious, keen to learn and proactive by nature
You are open to and value feedback in order to improve
Eligible to work in Tallinn or London (You can work from anywhere in the country you're hired!)
And these would be great, but aren’t essential:
Experience in applying causal inference and/or uplift modeling techniques, for example with DoWhy and EconML
Experience in designing and training deep neural networks
Experience in applying machine learning methods to real-world problems
Familiarity with TensorFlow 2 and/or PyTorch
Familiarity with AutoML frameworks, especially FLAML
Familiarity with Bayesian methods in machine learning
Experience in web development, from a previous internship
...Don’t worry we don’t expect you to know everything!
🙌Fun offices with social activities - have a sneak peak of life in our Singaporean office!
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.
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.