Staff Data Scientist

About the Role

Key Responsibilities

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

Requirements

• 6-10 years of 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 projects from prototyping, debugging, evaluation, optimization, deployment, to live monitoring.
• Knowledge of cutting-edge research in ML applications and deep learning.
• Ability to use SQL to answer key data questions quickly.
• Proficiency in scripting languages used in data science, such as Python and R.
• Enthusiasm for storytelling with data and understanding how data flows through systems to produce business outcomes.
• Strong curiosity about data problems and a commitment to thorough investigation.
• A love of science, the scientific method, and trust in scientific practitioners.

Nice to Have

• Experience with weak supervision and automated data labeling in ML systems.
• Knowledge of the advertising industry or digital media fraud detection.
• Experience working in a collaborative, research-driven environment.

Qualifications

• Educational background or certifications are not explicitly specified, but extensive experience in ML and data science is required.

Benefits & Perks

• Salary range for California applicants: $135,100 - $231,600, with actual pay varying based on experience and location.