Data Scientist/Machine Learning Engineer
Looking for Data Scientist/Machine Learning Engineer (Python, AWS, MySQL)
About the project
We are looking for a Data Scientist/ Machine Learning Engineer to join a company Information Extraction team.
The Information Extraction team is responsible for using machine learning to build the world’s largest cross-merchant purchase graph from email. They build engines for email classification and field extraction. They leverage existing open source technologies and established machine learning approaches, but also innovate and research new techniques. And of course, the company do all this on a large scale: hundreds of billions of documents.
As a data scientist / machine learning engineer, you will spend a mix of your time researching new solutions for information extraction as well as productionizing these solutions to make sure they work at scale. You will work with world-class data scientists who hold MS/PhD degrees from top global schools such as Stanford University, University of Washington, Carnegie Mellon University, and National Taiwan University, veterans from companies such as Microsoft, AOL, Yahoo!, and Twitter, as well as extremely talented and energetic junior data scientists.
• Expertise in Machine Learning
• Strong CS fundamentals, such as algorithms and data structures
• Expertise in Python
• Proficiency with relational databases such as MySQL
• BS or MS in a technical field
• Experience with cloud computing stacks such as Amazon Web Services preferred
• Excellent written and verbal communication skills
• Enthusiasm for working hard and having fun in a dynamic environment
• Team player with a keen interest in helping junior team members develop and grow
• Research and experiment with different machine learning algorithms and techniques
to find structure in unstructured documents
• Conduct design and code reviews
• Work with engineers to make sure the engines scale well on high volumes of data
• Work with the junior data scientists in Odessa to support their development and
• Collaborate with company remote data scientists and engineers based in the United States