Senior Applied Science Manager, GTS Network Design Analytics

- Ph.D. or Master's degree in Computer Science, Mathematics, Engineering, Statistics, Machine Learning or related field.
- Proven experience in broad Operations research/ML experience on large-scale industry problems in optimization, time series, forecasting.
- Several years of experience leading cross-functional tech teams
- Expertise in Local Search and deep learning methods
- A track record of balancing project delivery with longer term research, demonstrated via tracked business results.
- Proficiency in different programming languages such as Python, Julia, Java and frameworks like TensorFlow, PyTorch
- Proven written and verbal technical communication with the ability to present complex topics clearly to audiences with varying levels of technical familiarity
- Experience with devops praxis (CI/CD, telemetry, agile) and software systems design
- Experience delivering and scaling AI/ML based solutions involving Probabilistic Forecasting and neural Networks
- Experience building large scale Local Search solvers with nonlinear-constraints
- Experience of influencing business or company strategy through cutting edge research and long term science vision
- Experience partnering with academic institutions for collaborations and talent acquisition

Amazon is an equal opportunities employer. We believe passionately that employing a diverse workforce is central to our success. We make recruiting decisions based on your experience and skills. We value your passion to discover, invent, simplify and build. Protecting your privacy and the security of your data is a longstanding top priority for Amazon. Please consult our Privacy Notice (https://www.amazon.jobs/en/privacy_page) to know more about how we collect, use and transfer the personal data of our candidates.
Amazon's Global Transportation Services Network Design Analytics is seeking a Senior Applied Science Manager to build & lead an exceptional tech team in charge of devoloping the operations research models to design Amazon’s transportation network design with which we can keep offering the fastest and most cost-effective service to our customers.

We are looking for a talented, organized, and customer-focused leader to head a multidisciplinary team with Applied/Research Science, Data Science, Data Engineering, and Business Intelligence branches, with a charter to build optimization models and heuristics, ML models to infer KPI, pipelines holding models’s infrastructures, and connecting the dots between real operations and models formulation.

This role requires an individual with excellent team leadership skills, always-updated science breath/depth, outstanding business acumen, and an entrepreneurial spirit. We are looking for an experienced leader who is a self-starter comfortable with ambiguity, demonstrates strong attention to detail, and has the ability to work in a fast-paced and ever-changing environment.


Key job responsibilities
- Build the team. Lead and foster a highly talented group of applied/research/data scientists and data/business intel engineers that work together as a single unit. Establish internal and external talent acquisition opportunities.
- See the big picture. Shape long term vision for Amazon's science-based operations modelling and optimization
- Build strong collaborations. Partner with product, engineering, and science teams within Transportation and Supply Chain to deploy and connect models and services that connect different teams solutions at Amazon scale
- Stay informed. Establish mechanisms to stay up to date on latest scientific advancements in local search, linear/integer programming, algorithms, machine learning, neural networks, probabilistic forecasting/modelling,. Identify opportunities to apply them to relevant supply chain business problems
- Keep innovating for our customers. Foster an environment that promotes rapid experimentation, continuous learning, and incremental value delivery.

About the team
Within Global Transportation Services, the Network Design team leverages planet scale multi-modal data on Amazon shipments and capabilities to build advanced optimization and machine learning models. We preserve long term customer trust by ensuring Amazon's network is always as fast and cost-effective as possible.