• Algorithm Development: Create machine learning algorithms for scalable recommendation systems.
• Experimental Design: Rapidly design, prototype, and test hypotheses using quantitative analysis and business judgment.
• Integration: Work with software engineers to integrate experimental results into large-scale, low-latency production systems.
• Reporting: Present results with scientific rigor and business relevance, demonstrating good scientific practice in a business context.
• Education: PhD or Master’s degree in Computer Science, Computer Engineering, Machine Learning, or related field.
• Experience: Patents or publications in top-tier peer-reviewed conferences or journals.
• Programming: Proficiency in Java, C++, Python, or related languages.
• Skills: Experience with algorithms, data structures, numerical optimization, data mining, parallel and distributed computing, high-performance computing.
• Application: Experience in building machine learning models for business applications.
