We are open to hiring candidates to work out of one of the following locations:
Berlin – DE, London – UK, Luxembourg - LU
The Innovation & Engineering vision is to develop novel end-to-end process-centric and sustainable infrastructure concepts, striving to meet or even exceed current True North. The team is working against ambitious targets concerning All-in TPH, VCPP, space efficiency (shipments per sqm / cbm) and embodied carbon. The team consolidates SMEs to cover complex tasks concerning yard, MHE, UTR processes, container design and sustainability. Responsibilities encompass designing Yard and UTR infrastructure concepts, governing new builds or retrofits from Building Requirements Sheet to Design Reviews, developing functional requirements with ACES and WWDE, and supporting Procurement for vendor selection. Collaborating with NASC Engineering, the team designs Middle Mile Nodes using infrastructural models derived from analytical work.
This is a blue-sky role that gives you a chance to roll up your sleeves and dive into big data sets in order to build simulations and experimentation systems at scale, build optimization algorithms and leverage cutting-edge technologies across Amazon. This is an opportunity to think big about how to solve a challenging problem for the customers.
As a Sr. Simulation Engineer, you are an analytical problem solver who enjoys diving into data from various businesses, is excited about investigations and algorithms, can multi-task, and can credibly interface between scientists, engineers and business stakeholders. Your expertise in synthesizing and communicating insights and recommendations to audiences of varying levels of technical sophistication will enable you to answer specific business questions and innovate for the future. As a Sr. Simulation Engineer, you will apply cutting edge designs and methodologies for complex use cases across Middle Mile network to drive innovation. In addition, you will contribute to the end state vision for simulation and experimentation of future Sort centers at Amazon.
Key job responsibilities
• Design, develop, and simulate engineering solutions for complex yard and material handling challenges considering human/equipment interactions for the Last Mile network
• Lead and coordinate simulation efforts for optimal solutions through equipment specification, material flow, process design, ergonomics, associate experience, operational considerations and site layout
• The candidate must have the ability to work with diverse customer groups to solve business problems and provide data solutions that are organized and simple to understand
• Working close with team internal Subject matter Experts to drive analyze simulation results
• Working with technical and non-technical customers to design experiments, simulations, and communicate results
• Develop, document and update simulation standards, including standard results reports
• Create basic to highly advanced models and run "what-if" scenarios to help drive to optimal solutions
• Work closely with internal teams to ensure that every detail is thought through and documented using Standard Operating Procedures and/or structured change control
• Work closely with vendors, suppliers and other cross functional teams to come up with innovative solutions
• Simultaneously manage multiple projects and tasks while effectively influencing, negotiating, and communicating with internal and external business partners
• Conduct post-mortem on simulations, after implementation of new designs, in partnering with Safety and Operations
A day in the life
Starting from the Inbound vehicle and volume profile, indicators of the to be processed volume hourly distribution is available. This is the starting point for process centric design. Working backwards from minimum manual interactions with shipments, the Sr. Simulation Engineer has to create material flow concepts and evaluate them against True North processes, productivity and costs. Through simulation, specific business cases will be modeled by the Sr. Simulation Engineer and assessed with internal and external subject matter experts. Through simulation of alternative scenarios and identified areas to improve, concepts will be validated. An in depth report including clear recommendations and actions to meet the desired state will close the loop.
About the team
Amazon couldn’t deliver at pace without the Amazon Transportation Service (ATS) team. As part of ATS, you’ll be welcomed into a diverse team that plays a central role in our success. Using air, sea and road transport, as well as sortation centres equipped with the latest technology, you’ll help Amazon’s transport run at maximum efficiency. Our team captures data and uses it to drive decisions. They are key to making Amazon more innovative and efficient.
We put safety first as our people are our priority. And we use the expertise of our people to get packages to their destination – quickly, conveniently and sustainably.
We are open to hiring candidates to work out of one of the following locations:
London, GBR
BASIC QUALIFICATIONS
- Experience with data scripting languages (e.g., SQL, Python, R, or equivalent) or statistical/mathematical software (e.g., R, SAS, Matlab, or equivalent)
- Experience working as a Data Scientist
- Experience with statistical models e.g. multinomial logistic regression
- Bachelor’s degree in Industrial/ Mechanical/ Process Engineering A Bachelor or Master’s Degree in a highly quantitative field (Computer Science, Mechanical, Industrial Engineering, Machine Learning, Operational Research, Statistics, Mathematics, etc.)
- Tools: Experience in Emulate 3D, Altair, Hypermesh, NSS, AutoCAD and/or Flexsim
- Advanced experience in Discrete Event Simulation
- Coding in C# and/or any scripting languages
- Experience in Statistics
PREFERRED QUALIFICATIONS
- Experience with data visualization using Tableau, Quicksight, or similar tools
- Experience managing data pipelines
- Experience as a leader and mentor on a data science team
- Master's or PhD in Statistics, Applied Math, Operations Research, Economics, or a related quantitative field with working experience as a Data or Research Scientist.
- Proven experience with machine learning, statistical modeling, data mining, and analytics techniques.
- Proven experience with Discrete Event Simulation
- HTML, Java, or Visual Basic programming and interfacing knowledge
- Basic knowledge of material handling and storage systems
- Process improvement and facility flow experience
- Ability to be flexible and work independently in a fast-paced and rapidly changing environment
- Ability to effectively manage, influence, negotiate, and communicate with external business partners and internal teams to meet organizational capacity needs
