Staff Data Scientist

Description:

Integral Ad Science (IAS) is seeking a Staff Data Scientist to join its Fraud Detection team. IAS is a global leader in verification, optimization, and analytics solutions for the advertising industry. The role focuses on developing cutting-edge machine learning (ML) solutions to detect and mitigate invalid traffic (IVT) and fraud across digital platforms including web, mobile, connected TV (CTV), gaming, and social media.

Key Responsibilities:

• Lead innovative research to improve IVT detection accuracy and scope

• Collaborate with the Threat Lab to analyze evolving fraud schemes and develop quantitative solutions

• Build automated IVT detection systems leveraging ML and data science

• Communicate the business value of ML-driven fraud solutions to stakeholders

• Own projects end-to-end, from prototyping to deployment and monitoring

• Collaborate with engineers to integrate fraud detection systems into larger workflows

• Mentor junior data scientists and contribute to team knowledge

• Respond to internal and client incidents related to fraud detection

Required Qualifications:

• PhD or Master’s degree in quantitative fields such as mathematics, statistics, computer science, physics, economics, or computational neuroscience

• 6-10 years of experience applying ML and quantitative methods in a business context

• Practical experience building ML systems including weak supervision and automated data labeling

• End-to-end ownership of ML projects including debugging, evaluation, deployment, and monitoring

• Knowledge of cutting-edge ML and deep learning research

• Proficiency in SQL for data querying

• Expertise in Python or R for statistical computing

• Strong data storytelling skills and deep understanding of data flow and business impact

• Curiosity and scientific mindset

About Integral Ad Science:
IAS is a leading global platform that measures and optimizes digital media quality, ensuring ads reach real people in safe environments while maximizing advertiser ROI and publisher yield. IAS values diversity and inclusion and encourages applications from underrepresented groups.