Location: Barcelona, in-office 

At SumUp, we are passionate about giving access to financial services to the millions of businesses too small for most providers to consider. What started as one card reader has turned into a range of readers and multiple remote payment solutions, as well as banking services, including Business Accounts and Loans.

As a Senior Data Scientist in the Lending Tribe, you will play with a huge dataset with billions of transactions from millions of active users. From there, you will build impactful models to help businesses across multiple countries get access to credit through SumUp’s different lending products. You’ll be part of a team of talented analysts, engineers, and other scientists using an advanced stack of tools to create innovative solutions for our products.

What you will do:

• Improve the core lending models: credit risk scoring and affordability forecasting models using machine learning solutions
• Define data collection strategies and new algorithms for models to support expansion to new market segments
• Identify behavior trends from the data to create new models beyond credit risk assessment, such as fraud prevention, conversion prediction, and communication optimization
• Perform analyses and present your insights to enable SumUp business teams to make data-driven, mission-critical decisions 
• Communicate and present results to product and business stakeholders
• Mentor other Data Scientists to pursue data science excellence through good engineering practices

You will be great for this position if you have:

• 5+ years of experience as a Data Scientist
• Proficiency with Python and its scientific stack (pyspark, pandas, pytorch, scikit-learn)
• Solid SQL knowledge
• Mastery of statistics, machine learning, and probability theory
• Proven track record in delivering solutions end-to-end
• Experience deploying machine learning models and artifacts in production at scale
• Excellent technical reading, writing and communication skills to support stakeholder management

Big Plus:

• Experience with Credit Risk assessment
• Software engineering background: Embrace best practices with a passion for clean, maintainable, and testable code
• Degree in Data Science, Statistics, Mathematics, Economics, Computer Science, or a comparable degree

Why you should join SumUp:

• Opportunity to work with SumUppers globally on large-scale fintech products used by millions of businesses worldwide, from our Berlin office. This involves an office-first setup
• Restaurant tickets (powered by Edenred)
• Commitment to Diversity and Inclusion: Be part of a workplace that values and promotes diversity, fostering an inclusive environment where everyone's perspectives are respected and embraced
• A dedicated annual L&D budget of €2000 for attending conferences and/or advancing your career through further education
• 30 Days Sabbatical: Enjoy the unique opportunity to take a well-deserved break with our 30 days sabbatical benefit after completing 3 years of employment with SumUp
• Referral Bonus: Earn additional rewards by referring talented individuals to join the SumUp team

About SumUp

We believe in the everyday hero.

Small business owners are at the heart of all we do, so we create powerful, easy-to-use financial solutions to help them run their businesses. With a founder’s mentality and a 'team-first’ attitude, our diverse teams across Europe, South America and the United States work together to ensure that the small business owners we partner with can be successful doing what they love. 

SumUp is an Equal Employment Opportunity employer that proudly pursues and hires a diverse workforce. SumUp does not make hiring or employment decisions on the basis of race, colour, religion or religious belief, ethnic or national origin, nationality, sex, gender, gender identity, sexual orientation, disability, age or any other basis protected by applicable laws or prohibited by company policy. SumUp also strives for a healthy and safe workplace and strictly prohibits harassment of any kind.

SumUp will not accept unsolicited resumes from any source other than directly from a candidate.