Amazon Principal Applied Scientist Last Mile Science Analytics 

United States, Washington, Bellevue 

855586847

As a Principal Applied Scientist, you will:1. Address business challenges through building compelling cases and using data to influence change across the organization
2. Develop input and assumptions based on preexisting models to estimate costs and savings opportunities associated with varying levels of network growth and operations
3. Create metrics to measure business performance, identify root causes and trends, and prescribe action plans
4. Manage multiple high-impact projects simultaneously6. Communicate with and support various internal stakeholders and external audiences
7. Implement scheduling solutions, improve metrics, and develop scalable processes and tools- PhD in Operations Research, Statistics, Engineering, or Supply Chain Management
- Extensive experience in operations research and data-driven decision making
- Strong analytical and problem-solving skills
- Robust program management and research science skillsKey job responsibilities
1. Advanced Modeling and Algorithm Development:
- Design and implement sophisticated machine learning models for logistics optimization
2. AI and Machine Learning Integration:
- Architect and deploy AI-powered systems to enhance decision-making in logistics operations
- Implement deep learning techniques for image recognition in package sorting and handling
- Develop reinforcement learning algorithms for adaptive scheduling and resource management3. Big Data Analytics and Processing:
- Design and implement distributed computing solutions for processing massive logistics datasets
- Utilize cloud computing platforms (e.g., AWS) for scalable data processing and analysis5. AI-Driven Workflow Optimization:
- Design and implement AI agents for autonomous decision-making in logistics processes
6. Software Development and System Architecture:
- Write efficient, scalable code in languages such as Python, Java, or C++
- Develop and maintain complex software systems for logistics optimization
- Stay at the forefront of AI and ML research
- Publish research findings in top-tier conferences and journals

- 10+ years of building machine learning models or developing algorithms for business application experience
- PhD in engineering, technology, computer science, machine learning, robotics, operations research, statistics, mathematics or equivalent quantitative field, or 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

- PhD in engineering, technology, computer science, machine learning, robotics, operations research, statistics, mathematics or equivalent quantitative field
- 15+ years of relevant, broad research experience after PhD degree or equivalent.
- Deep expertise in Machine Learning
- Proficiency in programming for algorithm and code reviews.
- Strong core competency in mathematics and statistics.
- Track record of successful projects in algorithm design and product development.
- Publications at top-tier peer-reviewed conferences or journals.
- Strong prior experience with mentorship and/or management of senior scientists and engineers.
- Thinks strategically, but stays on top of tactical execution.
- Exhibits excellent business judgment; balances business, product, and technology very well.
- Effective verbal and written communication skills with non-technical and technical audiences.
- Experience working with real-world data sets and building scalable models from big data.
- 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.