About the job
DataVisor stands at the forefront of AI-driven fraud and risk management solutions, providing unparalleled detection capabilities within the industry. Our innovative SaaS platform allows for seamless integration and enhancement of diverse data sources, enabling organizations to respond to rapidly changing fraud and money laundering scenarios in real-time. With our proprietary unsupervised machine learning technology, robust device intelligence, and a powerful decision engine, we ensure substantial performance improvements from day one. Our platform is designed to accommodate a variety of applications across multiple business units, significantly reducing the total cost of ownership when compared to traditional point solutions. Recognized as a leader in our field, DataVisor is trusted by numerous Fortune 500 companies globally.
Our acclaimed software platform is driven by a team of top-tier professionals specializing in big data, machine learning, security, and scalable infrastructure. We foster a culture of openness, positivity, collaboration, and results-oriented work. Join us in transforming the future of fraud detection!
Position Overview:
As part of our platform engineering team, you will contribute to the development of a next-generation machine learning platform, integrating our unique unsupervised machine learning (UML) techniques with supervised machine learning (SML) algorithms. Your role will involve enhancing our core detection algorithms and automating the comprehensive training process.
With the rise of sophisticated fraud attacks, real-time detection is more crucial than ever. The platform team is tasked with constructing the architecture that supports real-time UML capabilities. We are seeking inventive and enthusiastic engineers to aid in the expansion of our novel streaming and database systems, which are essential for our detection functionalities.
Join us in pushing the limits of what is achievable in fraud detection and large-scale data processing, and help us introduce innovative solutions to this critical domain.
