Description

Build and scale recommendation and ranking systems to optimize sales outcomes and customer engagement.

This role is on-site.

Responsibilities

• Design and implement state-of-the-art recommender systems to identify high-intent companies and contacts.
• Identify key signals driving user actions using advanced probability, statistics, and reinforcement learning.
• Build new AI solutions and enhance existing models to drive continuous improvement.
• Partner with ML engineers to review technical designs and support the productionization of models and pipelines.
• Ensure scalability, reliability, and efficiency of data science models in real-world applications.

Required Skills

• MS with 5+ years of experience or PhD with 3+ years in Statistics, Applied Math, Computer Science, or Physics.
• 2+ years of experience building personalized recommender systems using deep learning, sequential algorithms, or reinforcement learning.
• Proficiency in writing readable, testable, and maintainable code in Python, SQL, and Spark.
• Experience with AI, APIs, and continuous model evaluation based on real-world feedback.
• Strong background in advanced statistical and analytic techniques.
• Proven ability to navigate large projects with multiple cross-functional collaborators and stakeholders.

Preferred Skills

• Experience with Ray.
• Deep experience with PyTorch, XGBoost, SparkML, Hugging Face model registries, and LLM APIs.

Key Skills

Education

ANY GRADUATE