Data Science - Shopping Experience Applied Research

Location: San Jose, CA, United States
Date Posted: 06-27-2016
Shopping Experience Applied Research Team is looking for a strong applied researcher / data scientist. The team works on heterogeneous data sets (behavioral, transaction and crawled data) and focuses on solving applied problems using Natural Language Processing, Text Mining, Data Mining & Machine Learning. The ideal candidate will have a nice blend of science 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 be strong at communication and capable of cross group collaborations. Experience in several of Spark/Hadoop, information extraction, text mining, information retrieval, machine learning learning, NLP is highly desirable. Job Requirements Our client is one of the largest online marketplaces in the world servings 100's of millions of customers. These customers engage with the platform and buy the most diverse merchandise from sellers all over the world. • The inventory ranges from a consumer selling her used t-shirt to some iconic merchandise sold by a few of the biggest brands on the planet. Due to the diverse nature of our sellers and corresponding inventory, we have a treasure trove of unstructured listings. • The Shopping Experience Applied Research Team's charter is to conduct applied research in various domains of shopping experience. The problems range from inventory understanding to insights mining, clustering to semantics understanding and from insight mining to building bottom up data driven products. • The Shopping Experience Applied Research Team also focuses on data problems in Search Engine Optimization which this particular role emphasizes on. • SEO charter is to ensure that buyers are able to discover merchandise available on our company site even when people start their search on a search engine like Google. Most of the company listings are ephemeral and disappear as items get sold which makes it difficult for search engines to understand inventory. • SEO team works on organizing the entire inventory in a slowly evolving structure that is easy for both buyers and search robots to understand and navigate. Also this structure needs to map to the intent expressed by buyers through their queries. • We are creating an end to end system that users large scale data mining and machine learning to organize buyer intents, aided with editorial validation to improve quality. This system will be the backbone of all merchandise browse and discovery solutions available at our company. What are we looking for? The ideal candidate has great machine learning background especially creating structure out of unstructured data. • Previous experience with information retrieval is highly desirable. • Passion for leveraging technical solutions aligned with long term strategy with incremental deliverable outputs would be appreciated. • Strong interpersonal communication and collaboration skills • Ability to work on data mining, data science projects with application engineering, quality engineers and product management. • Ability to mentor other data scientists and engineers. • Passion to stay on the cutting edge of data science.
Contact information:
Max Populi, LLC
4628 Bayard Street, #207
Pittsburgh, PA 15213-2750
Tel: (412) 567-5279
Fax: (412) 567-5198
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