Applied Scientist - Alexa Internet
- Seattle, WA
Alexa.com is seeking a creative, entrepreneurial, and customer-obsessed Applied Scientist who can apply cutting edge research and state-of-the-art machine learning algorithms to the development of scalable AI marketing analytics solutions. The ideal candidate has a broad and deep background in machine learning, is passionate about science, is highly driven to learn and deploy new technologies, thrives in a fast-paced environment that requires the development of solutions to ambiguous and challenging problems, and enjoys collaborating with both technical and nontechnical peers.
At Alexa.com, we solve ML problems in natural language processing and understanding, search relevance and ranking, and digital behavior measurement and prediction. As part of our AI team, you will work as a hands-on practitioner and technical leader in multiple areas such as statistical modeling, NLP and NLU, dimensionality reduction, and deep learning. You will formulate and test hypotheses, evaluate and implement ML techniques, and deliver new production services that will be used by millions of users worldwide.
We have been gathering and analyzing data from online sources for more than 20 years, with terabytes of archived crawl data, a data-contributing panel of millions of users in countries around the world, and millions of unique website visitors each month. This position provides the qualified candidate with an opportunity to join our smart, motivated team and to directly impact our business.
Alexa.com is a subsidiary of Amazon.com serving millions of users worldwide and building the next generation of marketing analytics services. Our mission is to be most invaluable and trusted source of ground-breaking insights into digital behavior that customers use to win their audience and accelerate growth. For more information, visit www.alexa.com.
• Develop novel modeling techniques for pattern recognition, prediction, classification, and other complex data science problems
• Develop prototypes and collaborate with stakeholders to assess the feasibility of selected approaches
• Write high quality code and contribute to our codebase of scientific applications using relevant technologies
• Build well-iterated models or analyses which reduce noise and maximize performance and accuracy
• Contribute to strategic planning and project management for a variety of technical initiatives
• Effectively communicate with customers, senior management, and colleagues with diverse roles and technical backgrounds
• Document methodologies and increase our institutional knowledge based on experimental results and operationalized solutions
• PhD or equivalent Master's Degree plus 4+ years of experience in CS, CE, ML or related field
• 2+ years of experience of building machine learning models for business application
• Experience programming in Java, C++, Python or related language
• Proficiency with a major programming language appropriate for data science such as Python, Scala, Java, or C++
• Expertise with a broad suite of machine learning techniques, natural language processing, and statistics
• A keen scientific mind with a proven ability to think critically and invent
• Experience with statistical and mathematical libraries and software
• Excellent oral and written communication skills and a strong discipline for documenting methodologies and applications
• A track record of thought leadership & contributions that have advanced the field
• Expertise in artificial intelligence techniques and methodologies
• Experience with modern methods for parallelized processing of large, distributed datasets (e.g. Spark, Hadoop, Map-reduce)
• Experience with AWS technologies such as EC2, S3, and Elastic Map Reduce, and ElasticSearch
• Peer-reviewed publications in top MLP, AI, or ML conferences or journals
• Experience working effectively with software engineering teams, product managers, and designers
• Experience working with web data (corpus of HTML documents, browse clickstreams, server logs)
• Proficiency with relational databases, Linux, and AWS solutions
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