About the Role

• We are looking for passion for developing state of the art Machine Learning based approaches for recommendations and monetization, and deploying them to production reliably and at scale. You will collaborate with product managers, applied researchers and engineers to invent, design and implement end-to-end reliable, scalable, efficient production services in Scala/Java, using state-of-the-art Big Data, Machine Learning, Deep Learning and Optimization techniques.
• The ideal candidate will have a blend of applied ML research and engineering skills, proven track record of solving critical business problems through data science and strong analytical/quantitative and engineering skills. The candidate will be expected to have strong communication skills and to be capable of cross-group collaborations.

Responsibilities:

• Track the state of art and help shape our applied research on recommender systems - both organic and sponsored
• Drive applied research in monetization of recommendations via first party ads by translating state of art into practical solutions
• Mentor data scientists and engineers in the application of ML, revenue optimization approaches
• Connect with senior data scientists in partner domains and drive key partnership initiatives
• Drive internal and external publications of applied research

Qualifications

• PhD in Machine Learning or related area
• 5-10 years professional experience post PhD
• Deep understanding of Machine Learning and Data Science
• Experience with applying ML to recommender systems at an enterprise scale
• Experience with sponsored recommendations and revenue optimization
• Applied research experience with a publication track record
• Familiarity with Big Data technologies such as Spark and Hadoop
• Good communication skills to convey ideas and solutions
• Ability to come up with good solutions quickly and prototype them rapidly
• Experience with guiding research teams and mentoring individual researchers
• Ability to prioritize business needs and pivot quickly if needed