About the role

Role overview

As a Senior Machine Learning Engineer at Step (full remote), you will design, develop, and deploy machine learning models to improve Risk and Fraud detection systems. You’ll lead technical work in this domain and collaborate closely with the Operations team.

Key missions

Conceive, develop, and deploy machine learning models for risk and fraud detection.
Provide technical leadership in the Risk/Fraud area and help shape the team’s strategy.
Use SQL to extract, transform, and manipulate data so it’s ready for model development.
Write production-grade code.
Design experiments to evaluate and improve model performance.
Partner with the Operations Team to support deployment and operational outcomes.

Requirements

Graduate degree in a technical field such as Statistics, Economics, Applied Mathematics, Computer Science, or a related discipline.
5+ years experience in Data Science or ML Engineering.
Proficiency in SQL and Python.
Experience developing and deploying machine learning models.
Excellent data analysis skills.
Ability to communicate clearly with both technical and non-technical stakeholders.

Nice-to-haves

Experience working in financial systems (e.g., lending, risk/fraud), though not required.

About Step

Step is a financial technology company focused on enhancing financial systems through technology. The role centers on improving Risk and Fraud detection by designing, developing, and deploying machine learning models.