Senior Data Scientist, Ratepay

• 5 + years of experience working with the whole data science product cycle: conception, research, prototyping, modelling, deployment to production
• Master’s degree in STEM field
• Very good engineering skills in Python and familiarity with clean code (pre-commit, black, code reviews etc.), unit testing (pytest) and type hints (mypy)
• General understanding of SQL and SQL databases. Ability to retrieve data and build data pipelines that feed models in research and (ideally) build pipelines for production
• Advanced knowledge of statistical learning theory and its application to solve real-world problems
• Strong stakeholder communication skills with the ability to clearly present ideas, solutions and findings

Desirable

• 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
• 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