Data Scientist

Company Description

Checkout.com is one of the most thrilling fintechs in the world. We are committed to helping businesses and their communities flourish in the digital economy. We are the strategic payments ally for several of the world's most well-known dynamic brands like Wise, Hut Group, Sony Electronics, Homebase, Henkel, Klarna and many others. Designed with performance and scalability as priority, our adaptable cloud-based payments platform helps international enterprises launch new products and create customer experiences that are loved. Our uniqueness lies not only in what we construct but also in our method.

We encourage determined problem-solvers to cooperate, innovate and give their utmost performance. That’s why we’re in the Forbes Cloud 100 list and are a Great Place to Work accredited company. And yet, we are just getting warmed up. We’re assembling diverse and inclusive teams across the globe — because we believe this leads us to design even better experiences for our merchants and partners. And we need your assistance. Join us and help shape the digital economy of tomorrow.

Job Description

About the Role

Checkout.com is seeking a data scientist to get involved in researching and developing Machine Learning (ML) models for fraud detection. These algorithms will deliver virtually instantaneous transaction risk predictions, which Checkout.com’s merchants can use to make smart payment routing decisions according to their risk tolerance.

You'll work alongside a resourceful team of data scientists and engineers, all focused on delivering scalable fraud detection ML models. Your main duty will be ML research. Your work will significantly impact a product area that is of high strategic value to Checkout.com.

Key Responsibilities

• Carry out original research into ML (or other statistical) methods for detecting fraud, which includes reading and implementing academic papers.
• Create, implement, and understand experiments in order to extract practical insights and improve model performance.
• Publish and present research findings to technical and non-technical audiences, both verbally and in writing.
• Write high-quality Python for feature engineering and model training.
• Promote the acquisition of new data and the enhancement of existing data sources.

Qualifications

About You

• PhD (or a Master's with industry research experience at the least) in a STEM subject (i.e. computer science, mathematics, physics, etc.).
• At least 2 years of experience developing machine learning models to address business challenges, with a primary focus on ML research.
• Experience with distributed computing technologies (e.g. Spark, Dask) for managing large data.
• Strong comprehension of machine learning, probability and statistics.
• Familiarity with applying scientific methodologies and thoughtful experimental design.
• Able to write high quality Python and SQL.

Nice to have

• Experience in fintech and/or payments.
• Experience with AWS or at least another popular cloud platform (GCP/Azure).
• Familiarity with the Unix shell and shell scripting (for task automation).

Additional Information