Data Science Lead (DSL1) - KYC Global & Onboarding

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.

More about our mission and what we offer.

Job Description

We’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.

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 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.

Qualifications

Additional 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

• Visa and relocation support 

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.