Your mission
Risk management is at the core of Ratepay’s business strategy. Our cutting-edge risk management platform processes hundreds of thousands of transactions daily, ensuring secure payments for our merchants and their customers while minimizing risk and maximizing profitability.
We are seeking a highly skilled and experienced Senior Full-Stack Data Scientist to take a leading role in enhancing our fraud prevention and credit risk assessment capabilities. This role involves researching, developing, and deploying advanced machine learning algorithms into production. You will be responsible for every aspect of the data science process, from data collection and pre-processing to building and deploying machine learning models, as well as developing and maintaining production-level codebases.
In this role, you will collaborate with cross-functional teams to drive innovation and ensure that our solutions are scalable and reliable in a fast-paced environment.
We are seeking a highly skilled and experienced Senior Full-Stack Data Scientist to take a leading role in enhancing our fraud prevention and credit risk assessment capabilities. This role involves researching, developing, and deploying advanced machine learning algorithms into production. You will be responsible for every aspect of the data science process, from data collection and pre-processing to building and deploying machine learning models, as well as developing and maintaining production-level codebases.
In this role, you will collaborate with cross-functional teams to drive innovation and ensure that our solutions are scalable and reliable in a fast-paced environment.
Your tasks at Ratepay, among others
- Lead the research, development and implementation of advanced machine learning models for credit risk assessment and fraud prevention.
- Own data science projects end-to-end, i.e. from ideation and proof of concept to bringing it into production.
- Write clean, efficient, and maintainable code adhering to best engineering practices for data processing, model development, and deployment, ensuring scalability and reliability.
- Pre-process complex financial data and create ETL pipelines to support machine learning models.
- Continuously improve our machine learning workflows, research, and deployment pipelines, ensuring best practices and innovation.
- Collaborate closely with team members and cross-functional teams, utilizing strong communication skills to develop robust machine learning solutions.
- Take ownership of subcomponents of the machine learning infrastructure, ensuring their performance and scalability as the platform evolves.