- Date Posted
- Jan. 11, 2022
- Data Science
At Wise our mission is Money Without Borders – instant, convenient, transparent and eventually free. Whether our customers are sending money to another country, spending money abroad, or making and receiving international business payments, Wise is on a mission to make their lives easier and save them money.
Here’s how you’ll be contributing to FinCrime
- You will help automate compliance operational decisions, digging into piles of data to find insights and create production grade models that can be clearly monitored by our operations team
- You will help the data science team develop models for financial risk mitigation through prototyping model features and develop them into production ready pipelines
- You will use the most recent tech stack (Airflow, AWS Sagemaker, Flink,Zeppelin, etc) to build machine-learning workflows for automatic model training, testing, monitoring and deployment ;
- Your average day will include building new models, maintaining production models, evaluating new ideas, putting out fires etc.
This role will give you the opportunity to:
- Have a direct impact – You will get behind the scene of company transactions, understand how we mitigate risk and at the same time provide our customers with the fast and fair service they deserve. What you build will have an impact on millions of customers.
- 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, product managers, engineers and operations across 4 Wise offices, a lot of video-calls and some travel is expected.
- Be part of our mission to make money without borders the new normal
- 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 have a Mathematics/Exact sciences/Engineering/finance background — for example, you’re comfortable with linear algebra and can easily follow the derivation of the backpropagation equations in a simple network ;
- You are familiar with a range of model types, and know when and why to use gradient boosting, neural networks, good old regression, or a blend of these ;
- 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 experienced in building machine learning models both on daily time series and on large data (100Ms of rows), using the right tools depending on the data volumes (our team uses Python, Spark, SQL, Kafka and sometimes Flink for shoveling data, but we’re open to others ) ;
- 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 are comfortable with visualising and communicating data to various audiences, you easily articulate and present your ideas.
Some extra skills that would be great:
You have previously worked as data scientist in compliance
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.