Data Scientist, Operations AI R&D

Key Skills

Java Programming, Python Programming, C++, SQL, Big Data Technology, Machine learning techniques, Data science techniques, Deep Learning, MATLAB Programming, Natural Language Processing (NLP), Amazon Athena, R Programming, Statistics, Data Modelling, AWS Sagemaker, Database testing, Amazon Simple Storage Service (S3), SAS, Mathematics, AWS Glue, Data Warehousing

Job Description

Are you looking for a challenge? Do you want to make a measurable impact by developing brand new AI and ML capabilities supporting Global Operations? Imagine being part of a team on the forefront of operational AI and ML to boldly research, develop, and quantify impact while designing systems to scale across operational variation. Our team lives at front of these new endeavors while going beyond current use AI and ML use cases in operations. We rapidly and scientifically experiment with systems, operators, and data sources to develop new impactful use cases for AI in the fulfillment operations arena. This experimentation is critical to defining human-in-the-loop AI labor requirements, operational and customer impact, and facilitating new robotic development all while balancing future technological needs.

Every time an Amazon customer makes a purchase, a number of operational systems are involved: from software systems to robotic handling to Amazon employees to automated vehicles. These systems are ripe for continued optimization, we leverage extensive data, small scale experiments, and developing technologies to establish brand new AI and ML uses. We are looking for data scientists to drive innovation in Advanced Technologies by pushing innovation through experimentation, developing new techniques and analytics for both AI and ML use cases, and applying existing models to our problem space and beyond. As an Amazon Data Scientist, your work will impact on how we serve our customers so that they get the right product at the right time. In our team, you will be working in an ambiguous environment with multiple of the world's largest data warehouse environments. You need to be a sophisticated user of data querying tools and advanced quantitative and modeling techniques, with the ability to synthesize and communicate insights and recommendations to audiences of varying levels of technical sophistication to drive change. Your work will be visible up to the highest business leaders in Robotics and Operations. You will perform deep dives across various system inputs/outputs and connect to key performance indicators through observational and simulation data, and detect anomalies to identify problems in our systems. Much of the job will require close collaboration with software development engineers, other scientists, and business teams to innovate for and solve problems of the future.

Key job responsibilities

• Working in an ambiguous environment with minimal direction.
• Helping to build production systems that take inputs from multiple models and make decisions in real time.
• Automating feedback loops for algorithms in production.
• Develop input and assumptions based preexisting models to estimate the costs and savings opportunities associated with varying levels of network growth and operations.
• Communicating with and supporting various internal stakeholders and external audiences.
• Utilizing Amazon systems and tools to effectively work with terabytes of data.

A day in the life

Bringing your authentic self to work, you interface with database specialists across operational teams in ambiguous problem spaces to experiment and find the biggest opportunities solvable by AI and ML. You ask questions and dive into data with a tenacity unmatched, and lead to scalable AI that positively impacts Amazon customers and our employees.

BASIC QUALIFICATIONS

• Masters in quantitative field (Computer Science, Mathematics, Machine Learning, AI, Statistics, or equivalent).
• Knowledge and expertise with Data modelling skills, SQL, and Columnar Databases.
• Skilled with Java, C++, or other programming language, as well as with R, SAS, MATLAB, Python or similar scripting language.
• 1-3 years of experience working in data science in a consumer product company, managing Machine Learning Scientists, Data Scientists, Research Scientists, Applied Scientists, Economists or equivalent fields.
• Ability to manage and quantify improvement in customer experience or value for the business resulting from research outcomes.

PREFERRED QUALIFICATIONS

• A PhD in a quantitative field (Computer Science, Mathematics, Machine Learning, AI, Statistics, or equivalent).
• 5+ years of experience working in data science in a consumer product company.
• Extensive knowledge and practical experience in several of the following areas: machine learning, statistics, NLP, deep learning, recommendation systems, dialogue systems, information retrieval.
• Functional knowledge of AWS platforms such as S3, Glue, Athena, Sagemaker.
• Ability to distill informal customer requirements into problem definitions, dealing with ambiguity and competing objectives.
• Demonstrated industry leadership in the fields of Database and/or Data Warehousing, Data Sciences and Big Data processing.
• Deep understanding of data, application, server, and network security.
• Excellent verbal and written communication skills, ability to convey rigorous mathematical concepts and considerations to non-experts.