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 DescriptionWe’re looking for a Data Science Lead to lead and develop our growing Verification Data Science team within KYC Global and Onboarding in London.
This role is a unique opportunity to understand the customer KYC domain, how we mitigate risk leveraging data science techniques, and at the same time how to provide our customers with the seamless experience they deserve. What you build will have a direct impact on Wise’s mission and millions of our customers.
Our verification team is responsible for the processes related to KYC (Know Your Customer) checks performed on consumers and businesses during onboarding. Within the team, our data scientists implement machine learning models and systems that support Document verification.
We are looking for someone to own the team’s data science roadmap, lead and develop our data scientists, and take responsibility for the impact and quality of our machine learning systems. You’ll provide technical direction across the model lifecycle, from training and testing to production performance and further improvements to our KYC systems.
Here’s how you’ll be contributing:
Own the data science roadmap and prioritise projects in collaboration with cross-functional teams, aligning the team’s work with customer needs and business goals.
Actively participate in planning and ideation of data science projects in collaboration with integrated cross-functional teams
Uncover opportunities and provide expertise on applying machine learning/data science techniques
Clearly articulate the value, limitations, and potential impact of data science initiatives to stakeholders with diverse levels of understanding
Manage and create large image and tabular datasets related to KYC processes
Iterate on our deep learning image models
Measure and optimize performance of our machine learning models
Maintain and develop a large Python codebase with industry-standard best practices
Keep up-to-date with the rapidly developing field of machine learning and research how to incorporate new ideas on systems that benefit our customers directly in production
Research the domain of Document verification to learn the best ways to prevent criminal activity
Manage and develop data scientists through coaching, regular feedback and career support, setting clear expectations and supporting hiring as the team grows.
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.
Additional InformationAdditional information
Key benefits:
Stock options in a profitable company
Hybrid working model - whether it’s working from home, working overseas, school plays or life admin we get that flexibility is essential
Annual personal development budget - whether it’s for books, courses, or conferences
You can read more about our full benefits package here...
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.
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.
Skills Required
- Expertise applying machine learning and data science techniques
- Experience with deep learning image models
- Experience managing large image and tabular datasets
- Strong Python development skills and experience maintaining production codebases
- Experience measuring and optimizing machine learning model performance
- Experience leading, coaching, and developing data scientists
- Ability to communicate data science value, limitations, and impact to diverse stakeholders
- Experience owning a data science roadmap and prioritizing cross-functional projects
Wise Compensation & Benefits Highlights
-
Leave & Time Off Breadth — Paid time off is considered generous, with substantial annual PTO, sick leave, and a paid sabbatical after four years highlighted. Feedback suggests these policies meaningfully support rest and flexibility.
-
Healthcare Strength — Health coverage is described as comprehensive, including medical, dental, vision, and options like HSA contributions and a zero-deductible plan in some cases. Feedback suggests the healthcare offering is viewed favorably overall.
-
Equity Value & Accessibility — Equity grants (RSUs or stock options) are broadly available and positioned as a core part of total compensation. Feedback suggests some employees find the equity a meaningful component of their overall package.
Wise Insights
What We Do
Wise is a global technology company, building the best way to move and manage the world's money. With Wise Account and Wise Business, people and businesses can hold 40 currencies, move money between countries and spend money abroad. Large companies and banks use Wise technology too; an entirely new network for the world's money. Launched in 2011, Wise is one of the world’s fastest growing, profitable tech companies. In fiscal year 2025, Wise supported around 15.6 million people and businesses, processing over $185 billion in cross-border transactions and saving customers around $2.6 billion.
Why Work With Us
We’re truly global in who we are, how we work, and how we build. Everything we do is centred around creating a world of money that’s fast, easy, fair. And open to all. Everyone who works here owns a piece of Wise, from the work they do, to the stock they hold.
Gallery
.jpg)
_0.jpg)
_0.jpg)
.jpg)
.jpg)
.jpg)
.jpg)
Wise Offices
Hybrid Workspace
Employees engage in a combination of remote and on-site work.
We expect new joiners in the office most days to build connections and learn from colleagues for their first six months. After that, most Wisers split their working week between the office and home, typically coming in at least 12 times a month.
