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Research Scientist, Alexa Local Information NLU

Job ID: 1785669 | Services LLC


Job summary
“Find a coffee shop between here and San Francisco,” “how much longer is target on main street open?,” “what is the next train to work,” “i need directions to the nearest gas station;” these are some of the utterances answered by the Alexa Local Information team. We enable customers to search for places, products, or services around them, and provide personalized travel, commute and navigation experiences to the places they find.

Our science team works at the intersection of ASR, NLU, Information Retrieval, Machine Learning and Big Data. We leverage techniques from all these fields to create novel algorithms that advance the state of the art in spoken language understanding and improve search quality for local Points of Interest (POI’s). Our work directly impacts the experience and engagement of customers who rely on Alexa to find relevant locations while in-the-car, on-the-go and at-home.

We are seeking a Research Scientist to be part of the NLU team within the Alexa Local Information Science group. This role requires collaborating closely with business, engineering and other scientists within Local Information and across the Alexa organization. You will work with a team of Language Engineers and scientists to launch new customer facing features and improve the current experiences.

Key job responsibilities
In this role you will:
· Perform hands-on data analysis and modeling with large data sets to develop insights that increase device usage and customer experience
· Apply Machine Learning and SLU techniques to improve our conversational interfaces and search algorithms
· Collaborate with Scientists and Language Engineers in developing coherent and comprehensive meaning representation frameworks
· Run A/B experiments, evaluate the impact of your optimizations and communicate your results to various business stakeholders
· Work closely with product managers and software engineers to design experiments and implement end-to-end solutions
· Setup and monitor alarms to detect anomalous data patterns and perform root cause analyses to explain and address them
· Be a member of the Amazon-wide Machine Learning Community, participating in internal and external MeetUps, Hackathons and Conferences
· Help attract and recruit technical talent


· PhD or equivalent Master's degree plus 4+ years of research experience in a quantitative field
· Experience investigating the feasibility of applying scientific principals and concepts to business problems and products
· Experience applying various machine learning techniques, and understanding the key parameters that affect their performance
· Experience developing experimental and analytic plans for data modeling processes, use of strong baselines, and the ability to accurately quantify performance via metrics or KPIs
· Experience working with speech and text language data
· Excellent verbal and written communication
· Able to think creatively and possess strong troubleshooting and problem solving skills
· Strong attention to detail
· Exceptional level of organization
· Thrive in a fast-paced, highly collaborative, dynamic work environment


· Experience with statistical language modeling
· Comfortable working with speech and text language data in multiple languages
· Practical knowledge of version control and agile development
· Familiarity with database queries and data analysis processes (SQL, R, Matlab, etc.)
· Willingness to support several projects at one time, and to accept reprioritization as necessary
· Experienced in writing academic-styled papers for presenting both the methodologies used and results for data science projects

Amazon is committed to a diverse and inclusive workplace. Amazon is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status. For individuals with disabilities who would like to request an accommodation, please visit