Head of Machine Learning – Fraud & Risk

Job not on LinkedIn

🕒 Yesterday

🏄 California – Remote

🏄 California – Remote

💵 $210k - $250k / year

⏰ Full Time

🔴 Lead

🤖 Machine Learning Engineer

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GTS Technology Solutions

WebsiteLinkedInAll Job Openings

51 - 200 employees

Founded 1984

🤖 Artificial Intelligence

🛍️ eCommerce

IT Consulting • Artificial Intelligence • eCommerce

GTS Technology Solutions is an IT consulting company specializing in helping businesses leverage technology to achieve their goals. Their team of experts provides a wide array of services, including IT strategy consulting, software development, data analytics, cloud solutions, and digital transformation. They focus on utilizing advanced technologies such as machine learning and AI to help clients optimize operations, drive growth, and enhance productivity in the digital age.

📋 Description

• 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.

🎯 Requirements

• 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.

🏖️ Benefits

• Competitive equity package • Comprehensive benefits • Visa sponsorship available for qualified candidates