Lead Data Scientist - KYC/onboarding

London, United Kingdom

Likely evergreen, first seen by us 5 days ago

Pay: GBP 90,500–127,000/year · Gross — pay source
Office: London, UK (Hybrid) Salary range: GBP 90.5K-127K yearly gross based on experience and interview outcomes* Key benefits:
Read the full posting
Work setting: Not stated
Employment: Full-time — employment source
Employment type in the employer’s posting: Full-time
From the employer’s posting

What you’ll work on

Our verification team is responsible for the processes related to KYC (Know Your Customer) checks performed on consumers and businesses during onboarding.

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.

Own training, testing and performance analysis of KYC machine learning models
Manage and create large image and tabular datasets for KYC processes
Iterate on deep learning image models and measure their performance
Maintain and develop a large Python codebase to industry best practices
Mentor junior team members in data science skills

From the employer’s posting

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.

own training, iteration, and management of our machine learning models’ life cycle

Manage and create large image and tabular datasets related to KYC processes

Iterate on our deep learning image models

Maintain and develop a large Python codebase with industry-standard best practices

Provide mentorship to junior team members, promoting their growth in data science skills

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Posting record

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Likely evergreenReposted 2 times since Oct 7, 2026. A role that keeps coming back is often kept open to collect applications rather than to fill one seat.

Status in our records: Live
First seen by us: Nov 2, 20265 days ago
Recorded sightings: 6
Last seen by us: Nov 7, 2026
Reposted: 2 times since Oct 7, 2026

These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications. We count a repost when the same title and location comes back as a new listing within 60 days of the last one coming down. Some hiring systems expire listings on a schedule, so repost rates vary by system.

How this job compares

Time since we first saw it

Day 5

Early. Similar jobs usually come down between day 7 and day 57.

At Wise, jobs usually come down by about day 11.

From 10,550 similar postings that came down, and 338 of Wise’s. Coming down is not always a hire.

Wise is hiring

53 open jobs

Open jobs by the week we first saw them, last 12 weeks.

Data Scientist hiring is steady
Takes jobs down quickly
36% of open jobs were reposted

Hiring record

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Python

Where the posting names them

- Measure and optimise 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

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Demand for Data Scientist roles

New Data Scientist postings at the employers we follow are down 3% over the last 5 weeks compared with the 5 before.

August 17Last week

Each bar is one week of new postings. The darkest bars are the last 5 weeks.

Counted from the hiring pages we’ve followed for at least five weeks, so employers we add don’t look like growth. Updated weekly.

About the role

We file this job under Data Scientist, by the work the posting describes.

Data scientists use statistics and models to answer harder questions, such as whether a change worked, what demand will look like next quarter, or which customers are likely to leave.

Postings usually ask for Python or R, SQL, statistics, experiment design and common machine learning methods.

Unlike an ML engineer, a data scientist's main output is often an analysis or a first model, not software running inside a product.

US government figures for data scientists

Median yearly pay, May 2025: $120,230
Expected change, 2025 to 2035: 34.6% more jobsagainst 3.5% for all jobs

Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-2051.

Job description

View original posting ↗

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.

Company Description

We’re looking for a technical Lead Data Scientist (IC3) to join our growing KYC (Know Your Customer) and Onboarding Team in London.

This role is a unique opportunity to understand the customer onboarding & Know Your Customer 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.

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 optimise 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.