Principal Data Scientist

About the role

Position: Staff / Principal Data Scientist

Location: Remote — United States / Canada

Comp: Competitive base + comprehensive benefits package

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

Overview

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

What We’re Looking For

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

Why This Role

High-growth environment with cutting edge tech! You’ll tackle machine learning problems where scale, latency, experimentation, and measurable business impact all matter. The role offers substantial technical ownership and the opportunity to influence how ML is built and deployed across a global platform processing massive volumes of transactions and user interactions.