Principal Data Scientist - Carter

About Carter:

Carter is rethinking adtech infrastructure from the ground up with a privacy-first, AI-powered platform transforming commerce media. Our platform enables sophisticated audience management, seamless campaign execution, and advanced monetization-while keeping data security and privacy at the core. We empower our partners to turn every customer interaction into a revenue-generating opportunity, leveraging AI, first-party data, and seamless integrations across the entire retail media ecosystem.

Position Overview:

We are seeking a Principal Data Scientist to architect and deploy machine learning systems that power real-time bidding, cross-channel budget allocation, incrementality measurement, and lifetime value optimization for Carter’s platform. You’ll mentor data scientists and data engineers, collaborate closely with product and engineering, and help shape Carter’s technical roadmap in the fast-evolving adtech landscape.

Candidates with experience in high-frequency, high-volume environments in adtech are especially encouraged to apply.

Job Responsibilities:

• Design and deploy scalable ML models for real-time bidding, campaign pacing, budget allocation, and cross-channel optimization
• Develop and implement frameworks for incrementality measurement, attribution, and customer lifetime value optimization using advanced causal inference and privacy-preserving techniques
• Mentor and guide a team of data scientists and data engineers, fostering technical excellence and collaboration
• Collaborate with engineering and product teams to translate business goals and advertiser KPIs into actionable data science solutions
• Ensure robust model monitoring, validation, and performance tracking in high-throughput, low-latency production environments
  
  
  

Basic Qualifications:

• 8+ years deploying machine learning models in high-volume adtech environments
• Deep expertise in classification models, reinforcement learning, real-time prediction, distributed training, and causal inference
• Proficient in Python, Scala, SQL, XGBoost and familiar with adtech protocols and privacy-preserving ML
• Proven success mentoring data science teams and translating business needs into ML solutions
• Excellent communicator across technical and non-technical teams
  
  
  

We are proud to offer a competitive salary alongside a strong healthcare insurance and benefits package. The role is ideally hybrid, with 2 days per week spent in our Toronto office, however we are accepting remote applications across North America. We pride ourselves on the growth of our employees, offering extensive learning and development resources.

ShyftLabs is an equal-opportunity employer committed to creating a safe, diverse and inclusive environment. We encourage qualified applicants of all backgrounds including ethnicity, religion, disability status, gender identity, sexual orientation, family status, age, nationality, and education levels to apply. If you are contacted for an interview and require accommodation during the interviewing process, please let us know.