Full Time Job
Principal Researcher - Recommendation
Hulu
- Paid
- Full Time
- Senior (5-10 years) Experience
Job Description
Hulu’s Research team is seeking a Principal Researcher who will be a thoughtful leader driving the future of recommendation research and development for online video. As a senior member of our research team, you will have a chance to tackle some of the most challenging and exciting algorithmic problems.
The recommendation team analyze and demonstrates petabytes of user and content data in order to serve the right content to the right users, and create the best personalization experience in online video. While we stand firmly on statistical and mathematical roots, we see great value real world, creative and pragmatic solutions.
An ideal candidate will be a role model for the research engineers and researchers, with a proven track record of working on large scale research projects that is deployed into highly scalable production systems.
WHAT YOU’LL DO
• Apply state of the art machine learning, statistics or data mining in a variety of areas, such as relevance prediction, user modeling, learning to ranking, and text mining
• Invent and fast iterate on novel solutions to challenging data related problems
• Develop scalable and efficient methods for large scale data analysis and model development
• Collaborate with developers, program managers, and product managers in an open, creative environment
WHAT TO BRING
• MS or PhD in computer science, EE or other quantitative discipline
• 5+ years of working experience on large scale machine learning, user behavior analysis, text mining in leading internet companies. Experience in personalization technology is highly preferred
• Familiarity with Java, Python, C/C++ or any other OOP language
• Proven track record of thriving in a fast-paced, data-driven, collaborative and iterative applied research environment
• Outstanding research track record in the areas of machine learning, data mining, or statistical modeling, with evidence through publications in renowned journals, conferences
• Excellent written and oral communication skills. Chinese Mandarin proficiency is required
Jobcode: Reference SBJ-gk2k94-174-129-93-231-42 in your application.