Data Science Lead - Screening

Compensation: GBP 85,000 - GBP 115,000 - yearly

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.

We’re looking for a Data Science Lead to join our Screening team in London. This role is a unique opportunity to work on building out the Data Science team and machine learning based technical solutions in the Screening team, which owns Sanctions, Adverse Media and Politically Exposed Persons screening. This is an exciting opportunity to develop the program in a global company. Your work will allow Wise to keep our customers safe and making sure we can keep our ecosystem free of bad actors in a scalable way. What you build will have a direct impact on Wise’s mission and millions of our customers.

About the Role:

In the Screening Squad we are aiming for an effective and efficient screening system to cover instant transfers for our international customers. In order to achieve this we need to make sure the Screening Data Science team is staffed properly and the technology is built in a way to support it. Since the team has only recently started looking into machine learning, NLP and GenAI use cases, there is a chance to build these systems from the start. In the near-term the team is mainly focused on bringing both effectiveness and efficiency gains to the Sanctions program by adoption of machine learning and GenAI technologies.

How you’ll be contributing:

• Sanctions Screening System Development

• Developing efficient and effective Sanctions screening controls
• Introducing a mixture of real‑time and batch processing solutions depending on the product needs
• Developing technologies to serve Wise’s diverse international user base
• Using a mixture of traditional machine learning and NLP systems with GenAI technologies

• Working with product managers and engineering leads to understand staffing requirements
• Hiring specialists
• Mentoring more junior members of the team on technical and non‑technical skillsets

• Evaluating our Screening systems against internal and external benchmarks
• Identifying and categorising system errors, and suggesting technical solutions to rectify these errors
• Fine‑tuning system settings to achieve an optimal balance between precision and recall
• Providing data‑driven insights on potential outcomes under various scenarios

• Collaborating with operational teams to refine processes, ensuring effective feedback integration into our automation systems
• Designing and managing projects that utilise excess operational capacity, such as manual data labelling for model improvement

• Integrating active learning strategies to continuously improve model accuracy through feedback loops

• Packaging algorithms into deployable libraries/objects and transitioning them from staging to production environments
• Implementing and maintaining scheduled processes for data gathering and model retraining using automated pipelines
• Maintaining production‑grade Python services

A bit about you

• Experience implementing, training, testing and evaluating performance of Machine Learning systems
• Strong Python knowledge. A big plus for proven familiarity and experience with OOP principles
• Knowledge and experience within the Screening domain (Sanctions, Politically Exposed Persons, Adverse Media)
• Experience with statistical analysis, and ability to produce well‑designed experiments
• A strong product mindset with the ability to work independently in a cross‑functional and cross‑team environment
• Good communication skills and ability to get the point across to non‑technical individuals
• Strong problem solving skills with the ability to help refine problem statements and figure out how to solve them

Some extra skills that are great (but not essential)

• Familiarity with automating operational processes via technical solutions, for example Large Language Models
• Willingness to get hands dirty with operational side by sides to understand their pain points

Additional Information

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.

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.