Junior Fraud Data Scientist

Company Description

We’re Checkout. com.

You might not know our name, but companies like e Bay, Spotify, Klarna, Uber, and Sony do, because we’re behind many of the digital experiences you use every day.

We are where the world checks out, enabling over 10 billion transactions yearly for more than one billion global shoppers.

Whether you want to book a holiday, order food, renew a subscription, or check out online, there’s a good chance our tech powers the payments behind the scenes.

Our platform helps the most ambitious businesses deliver effortless digital experiences, at scale.

If you want to do career-defining work, you’ve come to the right place.

We move fast, think globally, and believe great teams are built by hiring exceptional people with conviction, curiosity, and the desire to make an impact.

With 20 offices across six continents and London as our HQ, we’re shaping the future of fintech – and we’re just getting started.

About the Role

As a Junior Fraud Data Scientist, you will contribute to our ongoing efforts to protect our ecosystem from financial threats and abuse.

Working under the guidance of senior team members in a data-rich environment, you will assist in identifying malicious behaviors, support detection coverage, and help maintain our automated mitigation strategies.

This role is designed for an analytical professional with 1–2 years of experience who wants to build a deep expertise in adversarial data, learn from an experienced team, and develop their technical skills across modern cloud data platforms.

• What You Will Be Doing
• Exploratory Data Analysis: Support the team by mining behavioral and transactional datasets to help identify anomalies and emerging fraud patterns.
• Model Support & Optimization: Assist in building, tuning, and validating machine learning models (e. g., XGBoost, Light GBM) under the supervision of senior data scientists.
• Feature Generation: Extract, engineer, and prepare new data features from structured and unstructured sources to help improve model performance.
• Dashboarding & Monitoring: Build and maintain internal dashboards and pipelines to track model health, data drift, and key fraud KPIs.
• Cross-functional Collaboration: Work alongside Fraud Analytics and Product teams to help translate operational fraud insights into automated data solutions.

Requirements

• Experience: 1–2 years of hands-on professional experience as a Data Scientist or Data Analyst in a data-intensive environment.
• Data Science Tech Stack: Solid proficiency in Python (Pandas, Num Py, Scikit-Learn) and strong capability writing and optimizing SQL queries.
• Modern Data Infrastructure: Exposure to or basic hands-on experience working within environments like Databricks and data warehouses like Big Query.
• Academic Background: Degree in a quantitative field (Computer Science, Statistics, Data Science, Industrial Engineering, or equivalent).
• Business-Impact Focus: An understanding of how to look past raw model metrics (precision/recall) to appreciate the operational impact of data decisions.
• Communication: Fluent English with the ability to communicate technical findings clearly to team members.
• Bonus Points
• Prior exposure to or hands-on projects involving machine learning models in a live, real-time production environment.
• Familiarity with MLOps or orchestration tools such as MLflow or Airflow.
• Previous domain exposure in Fin Tech, e-commerce, payments, or trust & safety.
• Additional Information
• 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.

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.

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