Integral Ad Science (IAS) is looking for a Senior Data Scientist on the Fraud Team to drive innovative research and improve the accuracy and scope of their IVT (invalid traffic) detection capabilities across various platforms.
Requirements
- 4+ 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
- An innate curiosity about data problems, strongly held commitment to getting to the bottom of things
Responsibilities
- 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
Other
- PhD or masters in a quantitative discipline (e.g., mathematics, statistics, computer science, physics, economics, computational neuroscience)
- Enthusiasm for telling stories with data, deep understanding of how data works and flows through systems to produce business outcomes
- A love of science, the scientific method, and faith in your fellow practitioners in the scientific trade
- Respond to internal and client-facing incidents as they arise
