Research Scientist, Recommendation Systems

Job not on LinkedIn

🔥 4 minutes ago

🇺🇸 United States – Remote

⏰ Full Time

🟡 Mid-level

🟠 Senior

🧬 Research Scientist

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👻 Ghost score 12%

What it means: the chance that no one is really hiring for this job.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.Why this score:

• Just posted.
• Jobs at this company usually fill in 98 days.
• No salary listed.

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📋 Description

• Design, implement, and evaluate machine learning models for recommendation, ranking, and personalization • Conduct applied research to improve model quality, robustness, and efficiency • Develop and execute experimentation strategies using offline evaluation and online testing • Work with complex datasets to understand user behavior and system performance • Collaborate with engineering and product teams to transition research into production systems • Share research results in clear, accessible ways with both technical and non-technical audiences • Stay informed about advances in recommendation systems and related ML methodologies

🎯 Requirements

• Advanced degree (PhD or MS) in Computer Science, Machine Learning, Statistics, or a related field, or equivalent experience • Experience developing recommendation, ranking, or personalization models for user-generated content • Strong foundation in machine learning, statistics, and data analysis • Proficiency in Python and modern ML frameworks (e.g., PyTorch) • Ability to conduct independent research and collaborate effectively in team environments • Prior publications or submissions to RecSys or closely related venues • Experience working with large-scale data and computational systems • Experience with representation learning, sequence modeling, or large-scale optimization • Experience transitioning research prototypes into production systems

🏖️ Benefits

• Opportunity to shape product direction through data and cutting-edge research • Freedom to shape research direction and problem selection • Work closely with teammates across research, engineering, and product as the organization grows • Support for continued learning and professional growth • Competitive compensation and benefits

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