About the Role
Are you interested in how products are delivered to customers quickly and efficiently? The WW Amazon Logistics, Business Analytics team manages the delivery of millions of products weekly, ensuring on-time and cost-effective delivery. We are seeking an enthusiastic, customer-obsessed Sr. Applied Scientist with strong analytical skills to manage projects, implement scheduling solutions, improve metrics, and develop scalable processes and tools.
The primary role involves addressing business challenges by building compelling cases, influencing change across the organization using data, and making strategic, data-driven decisions. This role will significantly impact the customer experience by influencing the final phase of delivery at Amazon.
Ideal candidates will have a PhD in Operations Research, Statistics, Engineering, or Supply Chain, and be ready for challenging opportunities in our world-class operations. This role requires robust program management and research science skills to act on research outcomes, working both independently and collaboratively in ambiguous environments.
Responsibilities
- Develop inputs and assumptions based on preexisting models to estimate costs and savings opportunities related to network growth and operations.
- Create metrics to measure business performance, identify root causes and trends, and prescribe action plans.
- Manage multiple projects simultaneously.
- Work with technology teams and product managers to develop new tools and systems to support business growth.
- Communicate with and support various internal stakeholders and external audiences.
Basic Qualifications
- 10+ years of experience building machine learning models or developing algorithms for business applications.
- PhD in engineering, technology, computer science, machine learning, robotics, operations research, statistics, mathematics, or an equivalent quantitative field, OR a Master's degree and 10+ years of industry or academic research experience.
- Knowledge of programming languages such as C/C++, Python, Java, or Perl.
- Experience with neural deep learning methods and machine learning.
Preferred Qualifications
- PhD in engineering, technology, computer science, machine learning, robotics, operations research, statistics, mathematics, or an equivalent quantitative field.
- 6+ years of post-PhD experience.
- Knowledge of deep learning, machine learning, and statistics.
- 4+ years of scripting, programming, or security code review experience in a common language, such as Python, Java, or C++.
- Knowledge of mathematical/statistical/physics fundamentals.
- 5+ years of successful technology product work from ideation through launch.
- Experience in patents or publications at top-tier peer-reviewed conferences or journals.
- Experience in science or engineering team management.
- Experience establishing successful partnerships with internal and external teams to execute tactical initiatives.
- Experience shaping business strategy for technical products or services for large enterprises or partners.
- Experience in written and verbal communication skills to communicate with technical and non-technical audiences, including senior leadership.
- 4+ years of data science, business analytics, business intelligence, or similar experience in big data environments.
- Experience with modeling tools such as R, scikit-learn, Spark MLLib, MxNet, Tensorflow, numpy, scipy, etc.
- Experience with large-scale distributed systems such as Hadoop, Spark, etc.