About Ping Identity:

At Ping Identity, we're changing the way people think about enterprise security technology. With our innovative Identity Defined Security platform, we're helping to build a borderless world where people have total freedom to work wherever and however they want. Without friction. Without fear.

We call this digital freedom. And it's not just something we provide our customers. It's something that drives our company. People don't come here to join a culture that's built on digital freedom. They come to cultivate it.

We're headquartered in Denver, Colorado, and we have offices and employees around the globe. And we serve the largest, most demanding enterprises worldwide, including over half of the Fortune 100. Because even in the most complex enterprise environments, security shouldn't be a source of anxiety. It should be one of your greatest competitive advantages.

We are looking for a creative and passionate Fraud Researcher to join our detection team to work directly on our core technology. You will work with rich data and cutting edge technologies on numerous use cases such as bots, emulators, malicious human beavior and more. The team includes multi domain researchers and engineers. The position is based in Petah-Tikva (Hybrid).

Ping Identity Israel provides the next generation cloud-based Risk Management service which helps organisations make smarter authentication decisions using machine learning and analytics to detect malicious activity, by analysing multiple risk models.

You Will:

Work with Data Scientists, Researchers, Product Managers and Engineers to develop and validate advanced analytic techniques for security products Perform research and implementation and evaluation on various problems and use cases Threat intelligence and research in the grey and dark web. Research web and mobile fraud methods and techniques Research different data sources that can be used to identify fraudulent behaviours Lead end-to-end POCs for new fraud detection capabilities Clearly and concisely promote complex data analysis to various stakeholders