Integral Ad Science (IAS) is a global technology and data company that builds verification, optimization, and analytics solutions for the advertising industry and we’re looking for a Staff Data Scientist on the Fraud Team. If you are excited by technology that has the power to handle hundreds of thousands of transactions per second; collect tens of billions of events each day; and evaluate thousands of data points in real-time all while responding in just a few milliseconds, then IAS is the place for you!
As a Data Scientist, Fraud Detection at IAS, you will be part of a team that is at the center of innovation for the company and a major contributor to our core products. As part of the data science group at IAS, you will push the boundaries of applications of machine learning (ML) and deliver best-in-class solutions to serve our clients. Innovation is at the heart of our competitive advantage, and innovation starts with people and culture. You will join a group of data scientists committed to deep collaboration and high quality scientific research, ultimately producing a lasting impact on the IAS business.
The types of challenges we solve have attracted people from industry and academia with diverse backgrounds, ranging from ML, mathematics, physics, biology, neuroscience, and computer science to finance and economics. We’re passionate about maintaining an open and collaborative environment, where team members bring their own unique style of thinking and tools to the table.

What you’ll get to do:

• Drive innovative research within the data science fraud team, improve the accuracy and increase the scope of our IVT (invalid traffic) detection capabilities in web, mobile, CTV, gaming, social media etc.
• Collaborate with the Threat Lab, understand the nature of evolving fraud schemes and invent creative, quantitative solutions to identify and stop them
• Develop automated IVT detection systems based on science, data, and ML applications. Communicate the value they add to multiple stakeholders across the organization, socialize the predictive power and business value of data-driven ML
• Join a team of highly motivated ML researchers and developers, own projects from end-to-end, while collaborating with team members, learning, mentoring, contributing to the collective impact data science has on the IAS business
• Collaborate with engineers to integrate fraud solutions within larger engineering workflows
• Mentor junior data scientists to innovate and build high quality fraud solutions
• Respond to internal and client-facing incidents as they arise

YOU SHOULD APPLY IF YOU HAVE MOST OF THIS EXPERIENCE:

• PhD or masters in a quantitative discipline (e.g., mathematics, statistics, computer science, physics, economics, computational neuroscience)
• 6-10 years experience solving analytical problems using quantitative approaches and ML methods in a business environment
• Practical experience building ML systems, ideally using weak supervision and automated data labeling. End-to-end ownership of your work: from prototyping, debugging, evaluation, optimization, production deployment, to live monitoring
• Knowledge of cutting edge research in ML applications and deep learning
• Capable of using SQL to answer key data questions at the drop of a hat
• Expertise in standard scripting languages used in data science for statistical computation: Python, R
• Enthusiasm for telling stories with data, deep understanding of how data works and flows through systems to produce business outcomes
• An innate curiosity about data problems, strongly held commitment to getting to the bottom of things
• A love of science, the scientific method, and faith in your fellow practitioners in the scientific trade
  New York Applicants: The salary range for this position is $135,100 - $231,600. Actual pay may vary based on experience or geographic location.

• Drive innovative research within the data science fraud team, improve the accuracy and increase the scope of our IVT (invalid traffic) detection capabilities in web, mobile, CTV, gaming, social media etc.
• Collaborate with the Threat Lab, understand the nature of evolving fraud schemes and invent creative, quantitative solutions to identify and stop them
• Develop automated IVT detection systems based on science, data, and ML applications. Communicate the value they add to multiple stakeholders across the organization, socialize the predictive power and business value of data-driven ML
• Join a team of highly motivated ML researchers and developers, own projects from end-to-end, while collaborating with team members, learning, mentoring, contributing to the collective impact data science has on the IAS business
• Collaborate with engineers to integrate fraud solutions within larger engineering workflows
• Mentor junior data scientists to innovate and build high quality fraud solutions
• Respond to internal and client-facing incidents as they aris