At a Glance
- Tasks: Build machine learning models for Amazon's transportation planning systems and optimise operations.
- Company: Join Amazon's innovative Middle Mile Science group, a leader in freight transportation.
- Benefits: Competitive salary, diverse work culture, and opportunities for professional growth.
- Other info: Collaborative environment with a focus on diversity and inclusion.
- Why this job: Make a real impact on logistics with cutting-edge technology and innovative solutions.
- Qualifications: PhD or Master's with experience in programming and optimisation algorithms.
The predicted salary is between 60000 - 80000 € per year.
Amazon's Middle Mile Science group is looking for an Applied Scientist to build machine learning and optimization models for large-scale transportation planning systems. This includes the development of dynamic pricing and network planning models to improve operations and services for our external freight 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. Amazon often finds that existing techniques do not match our unique business needs, driving the innovation of new approaches and algorithms.
As an Applied Scientist focusing on external freight within middle mile transportation, you will work closely with business leaders, engineers, and fellow scientists to design and build scalable products operating across multiple transportation modes. You will create experiments and prototypes of new machine learning and optimization applications, present research findings to senior leadership, and implement your models within production systems. You will write production-quality code designed for scalability and maintainability, and make decisions that affect how we build and integrate algorithms across our product portfolio.
About The Team: Our Middle Mile Marketplace Science team builds the algorithms for Amazon’s rapidly growing freight marketplace. Amazon contracts with 3P shippers and a network of independent carriers, using a mix of contract structures with varying service and risk profiles. Our work focuses on mechanisms and learning algorithms to optimize pricing and matching in this complex marketplace, and continually improve the experience for carriers and shippers. This is an area with many challenging problems and a huge business impact for Amazon.
Basic Qualifications:
- Experience programming in Java, C++, Python or related language
- Experience with discrete and continuous optimization methodologies and algorithms
- PhD in engineering, technology, computer science, machine learning, robotics, operations research, statistics, mathematics, or equivalent quantitative field, or Master’s degree and 5+ years of industry or academic research experience
- 3+ years of building machine learning or optimization algorithms for business applications
Preferred Qualifications:
- Experience in professional software development
- Experience in standard machine-learning and statistical modeling tools and techniques (e.g. random forests, gradient-boosted regression, LASSO, logistic regression)
- Strong track record of publications at top-tier journals or conferences
- Experience with integer programming, dynamic programming, and/or stochastic optimization
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.
Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information.
Applied Scientist, Amazon Transportation employer: Amazon Science
At Amazon, we pride ourselves on fostering a dynamic and inclusive work environment where innovation thrives. As an Applied Scientist in our Middle Mile Science group, you will have the opportunity to work on cutting-edge machine learning and optimization models that directly impact our freight transportation network. With a strong emphasis on employee growth, collaboration with industry leaders, and a commitment to diversity, Amazon offers a unique platform for meaningful contributions and career advancement in a fast-paced, technology-driven setting.
StudySmarter Expert Advice🤫
We think this is how you could land Applied Scientist, Amazon Transportation
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, especially those at Amazon. LinkedIn is your best mate here – drop them a message, ask about their experiences, and see if they can give you the inside scoop on the Applied Scientist role.
✨Tip Number 2
Prepare for those technical interviews! Brush up on your programming skills in Java, C++, or Python, and get comfy with optimization algorithms. We recommend doing mock interviews with friends or using online platforms to simulate the real deal.
✨Tip Number 3
Show off your projects! If you've built any machine learning models or optimisation tools, make sure to have them ready to discuss. We love seeing practical applications of your skills, so be prepared to dive into the details during your interview.
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, it shows you’re serious about joining the Amazon team. Don’t forget to tailor your application to highlight your relevant experience!
We think you need these skills to ace Applied Scientist, Amazon Transportation
Some tips for your application 🫡
Tailor Your CV:Make sure your CV is tailored to the Applied Scientist role. Highlight your experience with machine learning and optimisation algorithms, and don’t forget to mention any relevant programming languages like Java, C++, or Python. We want to see how your skills match our needs!
Showcase Your Projects:Include specific projects where you've built machine learning models or optimisation systems. Describe the challenges you faced and how you overcame them. This gives us a glimpse into your problem-solving skills and creativity, which are super important for this role.
Be Clear and Concise:When writing your application, keep it clear and to the point. Use bullet points for easy reading and make sure to highlight your key achievements. We appreciate straightforward communication, especially when it comes to complex topics like optimisation and algorithms.
Apply Through Our Website:Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, it shows us that you’re serious about joining our team at Amazon's Middle Mile Science group.
How to prepare for a job interview at Amazon Science
✨Know Your Algorithms
Make sure you brush up on your knowledge of machine learning and optimisation algorithms. Be ready to discuss specific techniques you've used, like random forests or dynamic programming, and how they can be applied to real-world problems in transportation.
✨Showcase Your Coding Skills
Since you'll be writing production-quality code, it's crucial to demonstrate your programming skills during the interview. Prepare to solve coding challenges in languages like Python or Java, and explain your thought process as you go.
✨Prepare for Problem-Solving Questions
Expect to face questions that test your problem-solving abilities. Think about complex scenarios related to transportation planning and how you would approach them using optimisation models. Practice articulating your thought process clearly.
✨Engage with the Team's Vision
Familiarise yourself with Amazon's Middle Mile Science group and their goals. Be prepared to discuss how your experience aligns with their mission to improve freight operations and services. Showing genuine interest in their work can set you apart.
