Lead Data Scientist, Recommendations

What you'll do

• Provide technical leadership for machine learning systems powering digital recommendations and personalization.
• Design, develop, and deploy scalable recommendation, retrieval, ranking, and personalization models.
• Translate ambiguous business challenges into scalable algorithmic solutions that drive measurable impact.
• Manage the full project lifecycle from initial problem definition to production deployment and measurement.
• Establish best practices for model development, evaluation, and measurement across technical teams.
• Mentor other scientists and raise the technical bar within the data science organization.
• Implement advanced techniques including reinforcement learning and contextual bandit designs.
• Communicate complex technical concepts clearly to both technical and non-technical stakeholders.

What we're looking for

• PhD or MS in Computer Science, Machine Learning, Statistics, Applied Mathematics, Operations Research, or a related quantitative field.
• 2+ years of industry experience.
• 5+ years of experience developing machine learning solutions for recommendation, personalization, ranking, retrieval, or search systems.
• Experience with reinforcement learning and/or contextual bandit design, implementation, and evaluation.
• Strong programming skills in Python and SQL.
• Experience with deep learning frameworks such as PyTorch or JAX.
• Experience working with large-scale data processing and analytics platforms like Spark or equivalent.
• Deep understanding of machine learning, deep learning, optimization, statistics, probability, and experimental design.