The Amazon Global Communities (AGC) team’s primary charter is to build physical and digital communities for Amazon partners. The team has recently launched a social media platform for Amazon partners to collaborate and learn from each other and is looking for an experienced, self-starter, driven, and detail-oriented Applied Scientist to develop a roadmap, write requirements, and work with technical and non-technical stakeholders to build an Enterprise data science platform for internal business stakeholders to use and collaborate on a daily basis.
This charter requires the leader to build innovative matching and ranking solutions across very diverse categories, with an amazonian focus on our customers and on the long-term. We dive deep to figure out how customers interact with our social media technology, then we turn these learnings into innovative machine learned matching and ranking solutions to improve customer satisfaction and business metrics.
In this role you will leverage your strong background in Computer Science, Natural Language Processing, and Machine Learning to help build the next generation of our model development and assessment pipeline, harnessing and explaining rich data at Amazon scale, and providing automated insights to improve machine learned matchers and rankers that impact thousands of community managers each day. This role requires a pragmatic technical leader comfortable with ambiguity, capable of summarizing complex data and models through clear visual and written explanations. The candidate will have experience with machine learning models and information retrieval systems at scale. Additionally, we are seeking candidates with strong rigor in applied sciences and engineering, creativity, curiosity, and great judgment.
If this describes you, come join Amazon Global Communities. Our teams are using advances in search and information retrieval, machine learning, natural language processing, real-time and distributed systems to convert requirements into concrete deliverables. An Applied Scientist at Amazon will translate business and functional requirements into quick prototypes or proofs of concept. Comfort with a high degree of ambiguity and ability to solve problems that haven’t been solved to scale before are essential.
· A MS in CS, Machine Learning or in a highly quantitative field.
· 4+ years of hands-on experience in predictive modeling and large data analysis.
· Hands on development experience in Python, C++, Java, or other OOP language.
· A PhD in CS, Machine Learning or in a highly quantitative field.
· 6+ years of industry experience in predictive modeling and analysis
· Experience in applying machine learning, information retrieval, natural language processing to Search.
· Superior ML breadth and depth
· Strong record of publications in the area of information retrieval or natural language processing.
· Strong working knowledge of web-scale data processing (e.g., Hadoop, Spark).
· Strong problem solving ability.
· Strong verbal and written communications skills; experience presenting complex technical information, succinctly, to technical and business audiences