Welcome to RatePay – Europe's No. 1 white-label payment provider
Ratepay‘s risk management platform scans hundreds of thousands of transactions per day in order to enable secure payments for our merchants and their customers while also protecting our profitability. For this purpose, SW Engineers, Data Scientists, Data Engineers, ML Engineers and Product Managers closely collaborate in the Risk-engineering tribe to continuously enhance our risk management capabilities. How? By creating new in-house solutions for fraud prevention and credit risk assessment based on state-of-the-art machine learning, data processing, and the integration of third-party providers.
Currently operating on an on-premise setup for our ML use cases, we want to significantly improve our capabilities by augmenting our ML systems to suit our growing needs for automation, scalability and ease of use.
You would be one of the main contributors to implementing, operating, growing and improving our Risk platform as an AWS cloud-based solution. You will build and own large parts of our ML framework, such as features stores, data catalogs and automated feature generation with the goal to enable reliable ML delivery solutions at scale.
Furthermore, you partner closely with ML engineers, data scientists, analysts, software engineers and researchers to build reliable, distributed data pipelines and intuitive data products that feed into machine learning models, analytics & research, thereby allowing our stakeholders to easily leverage data in a self-serve manner.
Your Focus:
Data pipelines, features stores, feature generation + cloud
Ratepay‘s risk management platform scans hundreds of thousands of transactions per day in order to enable secure payments for our merchants and their customers while also protecting our profitability. For this purpose, SW Engineers, Data Scientists, Data Engineers, ML Engineers and Product Managers closely collaborate in the Risk-engineering tribe to continuously enhance our risk management capabilities. How? By creating new in-house solutions for fraud prevention and credit risk assessment based on state-of-the-art machine learning, data processing, and the integration of third-party providers.
Currently operating on an on-premise setup for our ML use cases, we want to significantly improve our capabilities by augmenting our ML systems to suit our growing needs for automation, scalability and ease of use.
You would be one of the main contributors to implementing, operating, growing and improving our Risk platform as an AWS cloud-based solution. You will build and own large parts of our ML framework, such as features stores, data catalogs and automated feature generation with the goal to enable reliable ML delivery solutions at scale.
Furthermore, you partner closely with ML engineers, data scientists, analysts, software engineers and researchers to build reliable, distributed data pipelines and intuitive data products that feed into machine learning models, analytics & research, thereby allowing our stakeholders to easily leverage data in a self-serve manner.
Your Focus:
Data pipelines, features stores, feature generation + cloud
- Together with a diverse, cross-functional team of Engineers and Data Scientists, you bring our Risk Decision Platform to the next level
- You build and own significant parts of our data engineering framework of our new to-be-built Machine Learning Platform by finding ways to create and improve scalable, efficient and well-tested solutions.
- You bring your improvement and automation ideas to life, shaping the future of data engineering at Ratepay