The Automated Profitability Management (APM) team, part of the Selling Partners Services (SPS) organization, improves the long term success of Amazon Retail by driving lower costs, and unlocking new product selection. Our team builds software and machine learning (ML) models to optimize contract negotiations between tens of thousands of vendors offering millions of products and Amazon. We directly influence the end-customer experience worldwide by determining the optimal combination of terms under which Amazon should acquire its inventory. We focus on product costs but also cover supply chain (Who pays the initial shipping costs?), marketing (Should a vendor fund advertising?), reverse-logistics (Who pays for damaged products? What about unsold inventory?) and more. Our mission is to provide to our customers the world's largest product assortment at competitive prices, through long term partnership with our vendors.
As a Science Manager in APM, you will manage a team of scientists to build ML models that solve various business challenges related to Amazon's vendor relationships and cost management. You will work with business leaders, scientists, and economists to translate business and functional requirements into concrete science deliverables, define the science vision and translate it into specific plans for the science team.
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. This role combines leadership, organizational ability, technical strength, product focus and business understanding.BASIC 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.
- 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