Principal Data Scientist

Summary

Join Carter, a company revolutionizing adtech infrastructure with a privacy-first AI-powered platform, as a Principal Data Scientist. You will design and deploy machine learning systems for real-time bidding, budget allocation, and customer lifetime value optimization. Mentoring data scientists and engineers, collaborating with product and engineering teams, and shaping Carter's technical roadmap are key aspects of this role. Candidates with adtech experience in high-frequency, high-volume environments are highly encouraged to apply. The position offers a competitive salary, strong healthcare insurance and benefits, and a hybrid work model with flexibility for remote work across North America. Extensive learning and development resources are also provided.

Requirements

• 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

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

Benefits

• Competitive salary
• Strong healthcare insurance and benefits package
• Hybrid work model with 2 days per week in Toronto office, remote applications across North America accepted
• Extensive learning and development resources