Lead Applied Data Scientist - Recommendations (Contextual Bandits, Reinforcement Learning)

What you'll do

• Lead recommendation and personalization projects from problem definition through production deployment and measurement.
• Set technical direction and best practices for model development, evaluation, and measurement; partner across data science, engineering, product, and business teams.
• Mentor scientists and promote collaboration and adoption of emerging machine learning methods.

What they ask for

• PhD or MS in a related quantitative field and 2+ years of industry experience.
• 5+ years developing machine learning solutions for recommendation, personalization, ranking, retrieval, or search systems at scale.
• Experience with reinforcement learning and/or contextual bandits, and leading the development, evaluation, and deployment of production ML solutions.
• Strong Python and SQL skills; experience with PyTorch or JAX, and large-scale data processing platforms such as Spark or equivalent.

Pay

$132,000.00 - $238,000.00 USD base salary

Tools

Python, SQL, PyTorch, JAX, Spark

AI focus

Develops recommendation and personalization machine learning systems, including reinforcement learning and/or contextual bandits; uses modern AI and generative AI tools to accelerate development, experimentation, and model delivery.