Principal Data Scientist

We’re looking for a Staff / Principal Data Scientist to help shape machine learning strategy for a global, high-scale digital commerce platform. This is a senior individual contributor role for someone who combines deep statistical and ML expertise with strong engineering rigor. You’ll work on complex problems across personalization, recommendations, fraud detection, advertising, experimentation, marketplace optimization, and predictive modeling.

This is not a research-only or API-integration role. We’re looking for someone who has personally built, trained, deployed, and improved sophisticated models operating in production.

What You’ll Do

• Architect and build production-grade ML models from problem definition through deployment and optimization
• Develop models across recommendation, personalization, fraud, ranking, advertising, churn/LTV, and marketplace optimization
• Own models in production, including monitoring, drift detection, retraining, latency, and inference performance
• Design rigorous experimentation and measurement frameworks to quantify business impact
• Establish ML architecture, evaluation standards, and technical best practices across teams
• Work with large-scale datasets and distributed ML/data infrastructure
• Provide technical leadership and mentorship to data scientists and ML engineers
• Evaluate emerging AI and LLM technologies and determine where they can create meaningful value

• Staff or Principal-level experience in applied machine learning or data science
• Advanced degree in Statistics, Machine Learning, Computer Science, Mathematics, Engineering, or a related quantitative field
• Deep hands-on experience building and training models rather than primarily integrating hosted APIs
• Proven experience deploying and owning ML models at significant production scale
• Strong foundation in supervised learning, deep learning, neural networks, gradient boosting, and statistical modeling
• Experience with recommendation systems, fraud/anomaly detection, ranking, personalization, advertising ML, or churn/LTV modeling
• Strong Python skills with frameworks such as PyTorch, TensorFlow, XGBoost/LightGBM, or scikit-learn
• Experience with modern MLOps practices, real-time systems, and low-latency production environments
• Ability to influence technical direction across teams while remaining deeply hands-on

Comp: Competitive base + comprehensive benefits package

Must Have: Deep hands-on experience building, deploying, and owning machine learning models in large-scale production environments