Head of Machine Learning (Fraud & Risk) – Remote at Glint Tech Solutions LLC

United States

$210k - $260k

<h2>About the Role</h2> <p>We are seeking an exceptional <strong>Head of Machine Learning</strong> to lead our Fraud &amp; 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.</p> <p>You&apos;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.</p> <p>This role is ideal for a hands-on technical leader who has successfully scaled ML products and teams in fast-growing startup environments.</p> <h2>Location</h2> <ul><li>Remote (United States)</li></ul> <h2>Compensation</h2> <ul><li><strong>&#x24;210,000 &#x2013; &#x24;250,000</strong> base salary</li><li>Exceptional candidates may be considered up to <strong>&#x24;260,000</strong></li><li>Competitive equity package</li><li>Comprehensive benefits</li><li>Visa sponsorship available for qualified candidates</li></ul> <h2>What You&apos;ll Do</h2> <ul><li>Lead the Fraud &amp; Risk Machine Learning organization, managing a team responsible for production fraud detection models.</li><li>Define and execute the machine learning roadmap for fraud prevention, identity verification, and risk decisioning.</li><li>Build and scale a portfolio of production ML models from concept through deployment and continuous optimization.</li><li>Partner with Product, Engineering, Risk, and Executive Leadership to solve complex business challenges using machine learning.</li><li>Drive end-to-end machine learning development including:<ul><li>Feature engineering</li><li>Data preparation</li><li>Model development</li><li>Validation</li><li>Production deployment</li><li>Monitoring and model performance optimization</li></ul></li><li>Establish best practices for model governance, experimentation, and production reliability.</li><li>Mentor and grow a high-performing team of Data Scientists and Machine Learning Engineers.</li><li>Provide technical leadership while remaining capable of contributing hands-on when necessary.</li><li>Present technical strategy, business impact, and model performance to executive stakeholders.</li></ul> <h2>Required Qualifications</h2> <ul><li>7&#x2013;15 years of experience in Applied Machine Learning or Data Science.</li><li>4+ years leading and managing Machine Learning or Data Science teams.</li><li>Proven success building and scaling production machine learning products in high-growth startup environments.</li><li>Experience leading teams responsible for ML systems that are core to the business.</li><li>Strong software engineering skills with production-level Python development.</li><li>Deep experience across the full machine learning lifecycle:<ul><li>Feature engineering</li><li>Model training</li><li>Model evaluation</li><li>Production deployment</li><li>Monitoring</li><li>Continuous improvement</li></ul></li><li>Domain expertise in one or more of the following:<ul><li>Fraud Detection</li><li>Financial Risk</li><li>Identity Verification</li><li>Cybersecurity</li></ul></li><li>Experience owning multiple production ML models rather than a single isolated project.</li><li>Strong leadership, communication, and stakeholder management skills.</li><li>Ability to communicate technical concepts clearly to executives and cross-functional partners.</li></ul> <h2>Preferred Qualifications</h2> <ul><li>Experience at high-growth startups (approximately 20&#x2013;400 employees).</li><li>Track record of scaling both machine learning products and engineering organizations.</li><li>Experience solving complex, high-impact business problems through machine learning.</li><li>Strong business acumen with the ability to align ML strategy to company objectives.</li><li>Demonstrated career progression into increasingly broader technical leadership roles.</li></ul> <h2>Education</h2> <ul><li>Master&apos;s or PhD in Computer Science, Statistics, Mathematics, Physics, Engineering, or another STEM discipline preferred.</li><li>Exceptional candidates with a Bachelor&apos;s degree and outstanding industry experience will also be considered.</li></ul> <h2>Ideal Candidate</h2> <p>We&apos;re looking for someone who:</p> <ul><li>Combines deep machine learning expertise with strong software engineering fundamentals.</li><li>Has built and deployed production ML systems at scale.</li><li>Can balance strategic leadership with technical depth.</li><li>Enjoys mentoring and developing high-performing teams.</li><li>Thrives in fast-paced startup environments.</li><li>Takes ownership of business outcomes&#x2014;not just model accuracy.</li><li>Is comfortable influencing technical direction and executive decision-making.</li></ul> <h2>Technical Skills</h2> <ul><li>Python</li><li>Machine Learning</li><li>Feature Engineering</li><li>Model Training &amp; Evaluation</li><li>Model Deployment &amp; Monitoring</li><li>Fraud Detection</li><li>Identity Verification</li><li>Financial Risk Modeling</li><li>Production ML Systems</li><li>Data Science</li><li>Software Engineering</li></ul>