Are you motivated to explore research in ambiguous spaces? Are you interested in conducting research that will improve the employee and manager experience at Amazon? Do you want to work on an interdisciplinary team of scientists that collaborate rather than compete? Join us at PXT Central Science!
The People eXperience and Technology Central Science Team (PXTCS) uses economics, behavioral science, statistics, and machine learning to proactively identify mechanisms and process improvements which simultaneously improve Amazon and the lives, wellbeing, and the value of work to Amazonians. We are an interdisciplinary team that combines the talents of science and engineering to develop and deliver solutions that measurably achieve this goal.
We are seeking a senior Applied Scientist with expertise in more than one or more of the following areas: machine learning, natural language processing, computational linguistics, algorithmic fairness, statistical inference, causal modeling, reinforcement learning, Bayesian methods, predictive analytics, decision theory, recommender systems, deep learning, time series modeling. In this role, you will lead and support research efforts within all aspects of the employee lifecycle: from candidate identification to recruiting, to onboarding and talent management, to leadership and development, to finally retention and brand advocacy upon exit.
The ideal candidate should have strong problem-solving skills, excellent business acumen, the ability to work independently and collaboratively, and have an expertise in both science and engineering. The ideal candidate is not methods-driven, but driven by the research question at hand; in other words, they will select the appropriate method for the problem, rather than searching for questions to answer with a preferred method. The candidate will need to navigate complex and ambiguous business challenges by asking the right questions, understanding what methodologies to employ, and communicating results to multiple audiences (e.g., technical peers, functional teams, business leaders).
About the team
We are a collegial and multidisciplinary team of researchers in People eXperience and Technology (PXT) that combines the talents of science and engineering to develop innovative solutions to make Amazon Earth's Best Employer. We leverage data and rigorous analysis to help Amazon attract, retain, and develop one of the world’s largest and most talented workforces.
• MS or PhD in Computer Science, Statistics, Math, Electrical Engineering, Computational Linguistics, Natural Language Processing, Economics, or related fields
• 5+ years of experience applying statistical/ML models in large-scale production applications
• Created production systems; 2+ years experience deploying solutions to AWS and/or hosting and maintaining AWS based production systems
• Skilled in Python, R or similar scripting language; knowledge of SQL
• Knowledge and practical experience in more than one of the following areas: machine learning, natural language processing, semantic parsing, statistical inference, causal modeling, reinforcement learning, Bayesian methods, predictive analytics, decision theory, recommender systems, deep learning, time series modeling
• Demonstrated use of modeling and optimization techniques tailored to meet business needs.
• Track record of solving ambiguous problems and delivering complex software systems to customers
• Excellent technical writing and communication skills and ability to convey scientific concepts to non-technical business audiences
• Highly adaptable, creative, and thrives in a fast-paced work environment
• Deep experience in several of the above areas and experience with libraries such as Tensorflow/MxNet/PyTorch
• Track record of publishing in premier journals and conferences
• Knowledge of software engineering best practices for the full software development life cycle (i.e., coding standards, code reviews, source control management, build processes, and testing)
• Familiarity with AWS and knowledge of distributed computing
• Experience with customer or employee sentiment data
• Experience with fact extraction, entity linking, question answering, semantic parsing, natural language generation, ontologies and knowledge representation--particularly for question answering.
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 https://www.amazon.jobs/en/disability/us.