The partner company is looking to build intelligent systems that protect users and the platform from risk and fraud by leading and scaling a machine learning engineering team
Requirements
- Strong proficiency in Python and SQL, with proven experience building and deploying ML models
- Solid background in data analysis, statistics, and experimental design
- Experience working with production machine learning systems
- Exposure to financial systems, lending, or risk and fraud use cases is a plus but not required
- 5 or more years of experience in data science or machine learning engineering
- Demonstrated leadership experience, including both technical guidance and people management
- Ability to communicate complex concepts clearly to both technical and non-technical stakeholders
Responsibilities
- Build, lead, and mentor a machine learning engineering team, taking a hands-on approach while assuming increasing management responsibilities as the team grows
- Design, develop, and deploy machine learning models to strengthen risk management and fraud detection capabilities
- Own technical direction within the risk and fraud domain, helping define strategy, architecture, and best practices
- Write production-quality code and ensure models are reliable, scalable, and maintainable
- Use SQL extensively to extract, transform, and prepare data for modeling and analysis
- Design experiments using sound statistical methods to evaluate performance and guide decision-making
- Partner closely with operations and other teams to respond rapidly to emerging risks and events
Other
- 5 or more years of experience in data science or machine learning engineering
- Demonstrated leadership experience, including both technical guidance and people management
- Ability to communicate complex concepts clearly to both technical and non-technical stakeholders
- Competitive salary based on experience
- Comprehensive medical and dental coverage
