Head of Machine Learning (Fraud & Risk) – Remote
About the Role
We are seeking an exceptional Head of Machine Learning to lead our Fraud & Risk Machine Learning organization. This is a highly visible leadership role responsible for building and scaling the next generation of fraud detection and risk decisioning products.
You'll lead a high-performing ML team while remaining technically credible, partnering closely with Product, Engineering, and Executive Leadership to develop production-grade machine learning systems that directly impact the business.
This role is ideal for a hands-on technical leader who has successfully scaled ML products and teams in fast-growing startup environments.
Location
- Remote (United States)
Compensation
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$210,000 – $250,000 base salary
- Exceptional candidates may be considered up to $260,000
- Competitive equity package
- Comprehensive benefits
- Visa sponsorship available for qualified candidates
What You'll Do
- Lead the Fraud & Risk Machine Learning organization, managing a team responsible for production fraud detection models.
- Define and execute the machine learning roadmap for fraud prevention, identity verification, and risk decisioning.
- Build and scale a portfolio of production ML models from concept through deployment and continuous optimization.
- Partner with Product, Engineering, Risk, and Executive Leadership to solve complex business challenges using machine learning.
- Drive end-to-end machine learning development including:
- Feature engineering
- Data preparation
- Model development
- Validation
- Production deployment
- Monitoring and model performance optimization
- Establish best practices for model governance, experimentation, and production reliability.
- Mentor and grow a high-performing team of Data Scientists and Machine Learning Engineers.
- Provide technical leadership while remaining capable of contributing hands-on when necessary.
- Present technical strategy, business impact, and model performance to executive stakeholders.
Required Qualifications
- 7–15 years of experience in Applied Machine Learning or Data Science.
- 4+ years leading and managing Machine Learning or Data Science teams.
- Proven success building and scaling production machine learning products in high-growth startup environments.
- Experience leading teams responsible for ML systems that are core to the business.
- Strong software engineering skills with production-level Python development.
- Deep experience across the full machine learning lifecycle:
- Feature engineering
- Model training
- Model evaluation
- Production deployment
- Monitoring
- Continuous improvement
- Domain expertise in one or more of the following:
- Fraud Detection
- Financial Risk
- Identity Verification
- Cybersecurity
- Experience owning multiple production ML models rather than a single isolated project.
- Strong leadership, communication, and stakeholder management skills.
- Ability to communicate technical concepts clearly to executives and cross-functional partners.
Preferred Qualifications
- Experience at high-growth startups (approximately 20–400 employees).
- Track record of scaling both machine learning products and engineering organizations.
- Experience solving complex, high-impact business problems through machine learning.
- Strong business acumen with the ability to align ML strategy to company objectives.
- Demonstrated career progression into increasingly broader technical leadership roles.
Education
- Master's or PhD in Computer Science, Statistics, Mathematics, Physics, Engineering, or another STEM discipline preferred.
- Exceptional candidates with a Bachelor's degree and outstanding industry experience will also be considered.
Ideal Candidate
We're looking for someone who:
- Combines deep machine learning expertise with strong software engineering fundamentals.
- Has built and deployed production ML systems at scale.
- Can balance strategic leadership with technical depth.
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