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Job Details

Checkout.com logo
FinTech

Senior Risk Data Scientist

at Checkout.com

ExperiencedNo visa sponsorship

Posted 17 days ago

No clicks

Senior Risk Data Scientist at Checkout.com responsible for developing rules and models to detect, prevent and manage risk across the payments portfolio. The role involves building and maintaining data-driven risk identification processes, devising advanced analytical methods to detect anomalies in large datasets, and developing/implementing Rating Scorecards and PD, LGD, EAD models. Strong SQL and programming (Python/R/JavaScript) skills and prior credit risk experience in payments or lending are required, along with maintaining and optimising credit risk reporting.

Compensation
Not specified

Currency: Not specified

City
London
Country
United Kingdom

Full Job Description

Company Description

We’re Checkout.com – you might not know our name, but companies like eBay, ASOS, Klarna, Uber Eats, and Sony do. That moment when you check out online? We make it happen.

Checkout.com is where the world checks out. Our global network powers billions of transactions every year, making money move without making a fuss. We spent years perfecting a service most people will never notice. Because when digital payments just work, businesses grow, customers stay, and no one stops to think about why.

With 19 offices spanning six continents, we feel at home everywhere – but London is our HQ. Wherever our people work their magic, they’re fast-moving, performance-obsessed, and driven by being better every day. Ideal. Because a role here isn’t just another job; it’s a career-defining opportunity to build the future of fintech.

Job Description

As a Senior Risk Data Scientist at Checkout.com, you will play a critical role in the Risk Team, developing rules and models to effectively detect, prevent and manage risk within the overall Checkout.com portfolio.

About You

  • Worked with large data sets in a data-driven environment.

  • Used SQL skills to extract and model data from a variety of data sources.

  • Programming language knowledge or experience (e.g. Python, R, Javascript) is essential.

  • Strong understanding of credit risk principles and has worked in either payments or lending environments previously.

  • Experience developing, maintaining and implementing PD, LGD, EAD models for ECL measurement purposes is preferred.

What you will be doing:

  • Build and maintain data-driven risk identification processes.

  • Devise advanced analytical methods to identify anomalies and patterns within large data sets.

  • Developing and implementing Rating Scorecards, PD, LGD, EAD models.

  • Maintain and optimise the current Credit Risk reporting system.

If you don't meet all the requirements but think you might still be right for the role, please apply anyway. We're always keen to speak to people who connect with our mission and values.


Bring all of you to work

We create the conditions for high performers to thrive – through real ownership, fewer blockers, and work that makes a difference from day one.

Here, you’ll move fast, take on meaningful challenges, and be recognized for the impact you deliver. It’s a place where ambition gets met with opportunity – and where your growth is in your hands.

We work as one team, and we back each other to succeed. So whatever your background or identity, if you’re ready to grow and make a difference, you’ll be right at home here.

It’s important we set you up for success and make our process as accessible as possible. So let us know in your application, or tell your recruiter directly, if you need anything to make your experience or working environment more comfortable.

Life at Checkout.com

We understand that work is just one part of your life. Our hybrid working model offers flexibility, with three days per week in the office to support collaboration and connection.

Curious about what it’s like to be part of our team? Visit our Careers Page to learn more about our culture, open roles, and what drives us.

For a closer look at daily life at Checkout.com, follow us on LinkedIn and Instagram

Job Details

Checkout.com logo
FinTech

17 days ago

clicks

Senior Risk Data Scientist

at Checkout.com

ExperiencedNo visa sponsorship

Not specified

Currency not set

City: London

Country: United Kingdom

Senior Risk Data Scientist at Checkout.com responsible for developing rules and models to detect, prevent and manage risk across the payments portfolio. The role involves building and maintaining data-driven risk identification processes, devising advanced analytical methods to detect anomalies in large datasets, and developing/implementing Rating Scorecards and PD, LGD, EAD models. Strong SQL and programming (Python/R/JavaScript) skills and prior credit risk experience in payments or lending are required, along with maintaining and optimising credit risk reporting.

Full Job Description

Company Description

We’re Checkout.com – you might not know our name, but companies like eBay, ASOS, Klarna, Uber Eats, and Sony do. That moment when you check out online? We make it happen.

Checkout.com is where the world checks out. Our global network powers billions of transactions every year, making money move without making a fuss. We spent years perfecting a service most people will never notice. Because when digital payments just work, businesses grow, customers stay, and no one stops to think about why.

With 19 offices spanning six continents, we feel at home everywhere – but London is our HQ. Wherever our people work their magic, they’re fast-moving, performance-obsessed, and driven by being better every day. Ideal. Because a role here isn’t just another job; it’s a career-defining opportunity to build the future of fintech.

Job Description

As a Senior Risk Data Scientist at Checkout.com, you will play a critical role in the Risk Team, developing rules and models to effectively detect, prevent and manage risk within the overall Checkout.com portfolio.

About You

  • Worked with large data sets in a data-driven environment.

  • Used SQL skills to extract and model data from a variety of data sources.

  • Programming language knowledge or experience (e.g. Python, R, Javascript) is essential.

  • Strong understanding of credit risk principles and has worked in either payments or lending environments previously.

  • Experience developing, maintaining and implementing PD, LGD, EAD models for ECL measurement purposes is preferred.

What you will be doing:

  • Build and maintain data-driven risk identification processes.

  • Devise advanced analytical methods to identify anomalies and patterns within large data sets.

  • Developing and implementing Rating Scorecards, PD, LGD, EAD models.

  • Maintain and optimise the current Credit Risk reporting system.

If you don't meet all the requirements but think you might still be right for the role, please apply anyway. We're always keen to speak to people who connect with our mission and values.


Bring all of you to work

We create the conditions for high performers to thrive – through real ownership, fewer blockers, and work that makes a difference from day one.

Here, you’ll move fast, take on meaningful challenges, and be recognized for the impact you deliver. It’s a place where ambition gets met with opportunity – and where your growth is in your hands.

We work as one team, and we back each other to succeed. So whatever your background or identity, if you’re ready to grow and make a difference, you’ll be right at home here.

It’s important we set you up for success and make our process as accessible as possible. So let us know in your application, or tell your recruiter directly, if you need anything to make your experience or working environment more comfortable.

Life at Checkout.com

We understand that work is just one part of your life. Our hybrid working model offers flexibility, with three days per week in the office to support collaboration and connection.

Curious about what it’s like to be part of our team? Visit our Careers Page to learn more about our culture, open roles, and what drives us.

For a closer look at daily life at Checkout.com, follow us on LinkedIn and Instagram