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- Tasks: Build machine learning models to optimise pricing and revenue for Amazon's freight business.
- Company: Join Amazon's innovative Middle Mile Science group, shaping the future of transportation.
- Benefits: Competitive salary, diverse work culture, and opportunities for professional growth.
- Other info: Collaborate with top talent and present your research to leadership.
- Why this job: Make a real impact on logistics with cutting-edge AI and optimisation techniques.
- Qualifications: PhD or Master's in a quantitative field and 5+ years of relevant experience.
The predicted salary is between 70000 - 90000 ÂŁ per year.
Amazon’s Middle Mile Science group is looking for a Senior Applied Scientist to build machine learning and optimization models to support pricing and revenue management of its external freight business. This includes the development of novel forecasting and dynamic pricing models as well as the application of causal inference and artificial intelligence techniques to improve marketplace services and execution for our customers.
The Middle Mile Science group develops optimization and machine learning systems that power Amazon’s freight transportation network, from network design and pricing to real‑time load planning and capacity utilization. The scale of Amazon’s fulfillment operations requires robust transportation networks that minimize cost while meeting all customer deadlines. Real‑time execution depends on state‑of‑the‑art optimization and artificial intelligence to coordinate thousands of operators and drivers. This includes shipper‑facing and carrier‑facing marketplace algorithms as well as network planning and optimization tools.
As a Senior Applied Scientist responsible for middle‑mile transportation, you will work closely with different teams—including business leaders and engineers—to design and build scalable products operating across multiple transportation modes. You will create experiments and prototype implementations of new learning algorithms and prediction techniques, have exposure to top‑level leadership to present findings of your research, and work closely with other scientists and engineers to implement your models within our production system.
Basic Qualifications:
- 5+ years of building machine learning models or developing algorithms for business applications
- 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
- Experience programming in Java, C++, Python or related language
- Experience in computer science fundamentals (object‑oriented design, data structures, algorithm design, problem solving and complexity analysis)
Preferred Qualifications:
- Experience with popular deep learning frameworks such as MxNet and TensorFlow
- Significant peer‑reviewed scientific contributions in premier journals and conferences
- Hands‑on experience with reinforcement learning and/or dynamic programming
- Experience working with AWS technologies
- Experience applying causal inference and/or experimental design to drive business decisions in large‑scale systems
Amazon is an equal opportunity employer. We believe passionately that employing a diverse workforce is central to our success. We make recruiting decisions based on your experience and skills. Protecting your privacy and the security of your data is a longstanding top priority for Amazon.
Sr. Applied Scientist, Amazon Transportation employer: Amazon Science
Contact Detail:
Amazon Science Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Sr. Applied Scientist, Amazon Transportation
✨Network Like a Pro
Get out there and connect with folks in the industry! Attend meetups, conferences, or even online webinars. The more people you know, the better your chances of landing that dream job.
✨Show Off Your Skills
Don’t just talk about your experience—show it! Create a portfolio or GitHub repository showcasing your machine learning models and algorithms. This gives potential employers a taste of what you can do.
✨Ace the Interview
Prepare for technical interviews by brushing up on your coding skills and algorithm design. Practice common interview questions and be ready to discuss your past projects in detail. Confidence is key!
✨Apply Through Our Website
Make sure to apply directly through our website for the best chance at getting noticed. We love seeing candidates who are proactive and genuinely interested in joining our team!
We think you need these skills to ace Sr. Applied Scientist, Amazon Transportation
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the role of Senior Applied Scientist. Highlight your experience with machine learning models and algorithms, especially those relevant to pricing and revenue management. We want to see how your skills align with our needs!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you're passionate about the role and how your background makes you a perfect fit for our Middle Mile Science group. Let us know what excites you about working with Amazon's freight marketplace.
Showcase Your Projects: If you've worked on any relevant projects, make sure to showcase them in your application. Whether it's a machine learning model or an optimisation algorithm, we love seeing real-world applications of your skills. Don’t forget to mention any innovative approaches you’ve taken!
Apply Through Our Website: We encourage you to apply through our website for the best chance of getting noticed. It’s the easiest way for us to track your application and ensure it reaches the right team. Plus, it shows you’re serious about joining us at Amazon!
How to prepare for a job interview at Amazon Science
✨Know Your Algorithms
Make sure you brush up on your knowledge of machine learning algorithms and optimization techniques. Be ready to discuss how you've applied these in past projects, especially in relation to pricing and revenue management.
✨Showcase Your Coding Skills
Since programming is key for this role, practice coding problems in Java, C++, or Python. You might be asked to solve a problem on the spot, so being comfortable with data structures and algorithm design will give you an edge.
✨Prepare for Technical Questions
Expect questions that dive deep into your experience with causal inference and experimental design. Have examples ready that demonstrate how you've used these techniques to drive business decisions in large-scale systems.
✨Engage with the Team's Vision
Research Amazon's Middle Mile Science group and understand their goals. Be prepared to discuss how your skills align with their mission to optimise freight transportation and improve marketplace services. Showing genuine interest can set you apart!