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 technical Lead Data Scientist (IC3) to join our growing KYC Global and Onboarding Team 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.
About the Role:
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 training, iteration, and management of our machine learning models’ life cycle, and be responsible for the overall training, testing, model performance analysis, and research further modifications to our KYC systems.
Here’s how you’ll be contributing:
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
Provide mentorship to junior team members, promoting their growth in data science skills and adherence to industry standards
Office: London, UK (Hybrid)
Salary range: GBP 90.5K-127K yearly gross based on experience and interview outcomes*
Key benefits:
Flexible working - whether it’s working from home, school plays or life admin we get that flexibility is essential and you’re trusted to do the right thing and be responsible
Stock options in a profitable company
Relocation support
Generous parental leave
Pension scheme
Paid sabbatical
Loads of development opportunities
Sports and wellbeing compensation
A fun work environment with social activities and events
The opportunity to work with super smart, curious people
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.
Keep up to date with life at Wise by following us on LinkedIn and Instagram.
Additional InformationFor 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
- Experience maintaining and developing large Python codebases
- Experience building and iterating deep learning image models
- Experience with machine learning model training, testing, lifecycle management and performance optimization
- Experience managing large image and tabular datasets
- Domain knowledge or experience in KYC, document verification, or fraud prevention
- Ability to mentor and grow junior data scientists
- Strong communication skills to explain ML value, limitations, and impact to stakeholders
- Based in or able to work from London office (hybrid)
What the Team is Saying
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Wise Compensation & Benefits Highlights
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Leave & Time Off Breadth — Global paid time off is presented as 33–36 days including local public holidays, plus three “Me Days,” with a paid six‑week sabbatical and stipend after four years. Work-from-anywhere for up to 90 days per year after six months further complements time away and flexibility.
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Equity Value & Accessibility — RSUs are granted to all employees, enabling broad ownership in the company. Equity is positioned as a standard, company‑wide component of total rewards.
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Parental & Family Support — Parental leave is described as generous across markets, with U.S. pages listing up to 18 weeks fully paid for birthing parents and 8 weeks for non‑birthing parents. Additional family‑oriented supports such as onsite Mother’s Rooms and abortion travel benefits are noted in certain locations.
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.
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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.
