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Hook

Research Scientist, Recommendation Systems

Hook

. Design, implement, and evaluate machine learning models for recommendation, ranking, and personalization .

Posted 11/11/2026full-timeRemote • United StatesMid-LevelSeniorWebsite

Core Competencies

Role fit
Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates expertise in designing and implementing machine learning models for recommendation systems, with a strong foundation in statistics and data analysis. Proficient in transitioning research into production systems while effectively collaborating with cross-functional teams.

Highest-signal resume keywords
Machine Learning Model DevelopmentPython ProficiencyRecommendation Systems ExpertiseIndependent Research CapabilityLarge-Scale Data Experience

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills
Machine LearningStatisticsData AnalysisRecommendation ModelsRanking ModelsPersonalization ModelsRepresentation LearningSequence ModelingLarge-Scale OptimizationExperimentation Strategies
Soft Skills
CollaborationEffective Communication
Tools & Technologies
PyTorchComputational Systems
Certifications & Qualifications
Advanced Degree in Computer ScienceAdvanced Degree in Machine LearningAdvanced Degree in Statistics
Industry Keywords
User-Generated ContentResearch PrototypesRecSysModel QualityModel RobustnessModel Efficiency

Tech Stack

Tools & technologies
PythonPyTorch

About the role

Key responsibilities & impact
  • 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

What you’ll need
  • 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

Comp & perks
  • 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