Machine Learning Scientist

About the role

Mitek (NASDAQ: MITK) is a global leader in digital & biometric identity authentication, fraud prevention, and mobile deposit solutions. Our verified identity platform and advanced image capture solutions are built on the latest advancements in biometric recognition, artificial intelligence, computer vision and machine learning, and trusted by over 7,500 organizations worldwide. We are headquartered in San Diego, California, with operations in the United Kingdom, Spain, France, Mexico, and the Netherlands. Visit us at www.miteksystems.com.

We are Virtual 1st! Whether you choose to work remotely from your home office or in-person from one of Mitek’s offices, our practices, processes and tools are designed to enable your success. At Mitek, the Future of Work is about flexibility and preference wherever and whenever we are working. Because we care about our candidates, employees and customers, we include an in-person meeting as part of our hiring process. It’s one of the ways we live our mission to “Protect What’s Real.”

At Mitek, we believe that teams are more resilient, effective, and innovative when they benefit from a wide range of ideas, lived experiences, and perspectives. The strength of our organization is deeply rooted in the people who power it.​ We know that a workforce reflecting the richness of our communities and customers helps us better serve their needs.

As a member of Mitek’s team, you will build machine learning solutions that improve fraud detection and explainability across our digital identity products.

You will combine different sources of evidence, explore complex patterns and relationships in large-scale data, and develop reliable models that support better fraud decisions.

You will work closely with Product and Fraud Domain Experts to understand emerging fraud challenges and collaborate with Data Engineering to turn promising ideas into scalable production capabilities.

We are looking for a hands-on Senior Data Scientist with strong machine learning fundamentals, curiosity to explore new approaches, and a practical mindset focused on delivering measurable business value.

What You Will Do -

Design, develop, and evaluate machine learning models for fraud detection, including fraud scoring and ensemble models that combine multiple sources of evidence.

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Analyze large-scale datasets to identify complex patterns, relationships, behaviors, and anomalies, developing new signals to improve fraud detection.

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Define robust experimentation and evaluation methodologies, including model calibration, operating thresholds, and performance metrics under realistic production conditions.

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Develop interpretable and explainable ML approaches that help internal stakeholders and customers understand fraud scores and decisions.

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Explore innovative approaches to fraud decisioning, including human-in-the-loop techniques and causal methods.