The ideal candidate will have a PhD in Mathematics, Statistics, Machine Learning, Economics, or a related quantitative field, and 5+ years of relevant work experience, including:
· Proven track record of achievements in natural language processing, search and personalization.
· Expertize on a broad set of ML approaches and techniques, ranging from Artificial Neural Networks to Bayesian Non-Parametrics methods.
· Experience in Structured Prediction and Dimensionality Reduction.
· Strong fundamentals in problem solving, algorithm design and complexity analysis.
· Proficiency in at least one scripting languages (e.g. Python) and one large-scale data processing platform (e.g. Hadoop, Hive, Spark).
· Experience with using could technologies (e.g. S3, Dynamo DB, Elastic Search) and experience in data warehousing.
· Strong personal interest in learning, researching, and creating new technologies with high commercial impact.