The Economic Technology team (ET) applies Machine Learning, Causal Inference, and Economic Methodologies to derive actionable insights about the complex economy of Amazon's retail business and to develop algorithms to drive strategic business decisions and improve operations. We are an interdisciplinary team of Economists, Engineers, and Scientists incubating and building day one solutions using cutting-edge technology, to solve some of the toughest business problems at Amazon.
This is a unique, high visibility opportunity for someone who wants to have business impact, dive deep into large-scale economic problems, enable measurable actions on the Consumer economy, and work closely with scientists and economists. If you are interested in Machine Learning, Reinforcement Learning, large-scale, low-latency distributed systems and can lead a team to build the software that use the models, this is the role you have been looking for.
We are a Day 1 team, with a charter to be disruptive through the use of ML and bridge the Science and Engineering gaps that exist for engineers today. You will start on green field projects working closely with Principal Scientists, Product Managers and leadership to bring our models to life. You will manage a team of 6-10 scientists and engineers, foster an agile development environment, champion operational and engineering excellence delivering world class, Amazon scale, solutions.
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/usBASIC QUALIFICATIONS
• Master's degree in Research, Computer Science, Applied Mathematics, or a closely related field.
• 5+ years related work experience in areas such as computer vision, data analytics, data modeling or machine learning.
• 3+ years of direct people management experience including duties such as performance evaluation and career development.
• Experience modeling and optimization techniques tailored to meet business needs and proven achievements in production systems.
• Experience as leader of a science team and developing junior members from academia/industry to a business environment.
• Knowledge of various machine learning techniques and key parameters that affect their performance.
• Excellent written and verbal communication skills.PREFERRED QUALIFICATIONS
• Experience building large-scale machine-learning systems that support batch, online and streaming architectures
• Experience with Big Data technologies such as AWS, Hadoop, Spark
• Experience building complex software systems that have been successfully delivered to customers
• Knowledge of professional software engineering practices & best practices for the full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations
• Experience with machine learning, data mining, and/or statistical analysis tools and engineering.
• Ph.D. in Computer Science, Computer Engineering, Electrical Engineering, Applied Mathematics, or a closely related field.
• A passion for innovation and raising the bar in teams, technology and projects
• An analytical mind that thrives in a data-driven environment
• Strong organizational planning and development, business judgment, technical leadership, and communication skills