-Communicate with business/engineering teams or clients to gather requirements, and solve business problems.
-Study/apply/tailor machine learning to systematically explore and predict user behavior with ad response data for extracting actionable insights and building large scale data products.
-Design data visualizations for clearly delivering analytic results to both business and technical audiences.
-Write well-organized reports, prepare impressive slides for presentations, and contribute to communities including publishing papers.
-MS/PhD in Computer Science, Statistics, Math, Physics, related technical fields or equivalent practical experiences.
-Strong collaboration/communication skills with multi-disciplinary teams, including business and engineering.
-Expertise in exploratory data analysis and machine learning and/or statistical inference, with fair understanding details under the hood and good balance between methodology and practice.
-Coding, coding, coding in Python or R.
-Efficient in SQL-like data query.
-Linux, Git/GitLab and cloud computing experience, such as AWS, GCP, is a plus.
-Hadoop ecosystem experience, such as Spark, Hive, is a plus.
-Hands-on designing/implementing end-to-end data ETL pipeline experience is a plus.
-Building insights dashboards experience using, for example Tableau is a plus.
-Extra points on keeping up with the state-of-the-art machine learning and data analytics technologies, and learning how to learn.
-Advertising/marketing industry experience is a plus.
-Publication experience is a plus.
-Fluent English is must.