Simulation Data Scientist, AT-Systems Engineering and Analytics

Key Skills

Java Programming, Python Programming, SQL, Apache Hadoop, Apache Hive

Job Description

Job summary

AT-SEA is seeking an exceptionally talented person who wants to explore the future of fulfillment through simulation. As Advanced Technology explores new approaches to automate transformations within the warehouse environment there is a distinct need to simulate complex systems in a realistic manner to determine if the design parameters will deliver the performance expected at scale. As physical testing begins to replace assumptions with data, the simulations will reveal whether there is a risk to the system not delivering expected performance. As improvements and mitigations are contemplated, the simulations will reveal which hold the greatest promise. Most of this work is expected to be conducted using industry standard tools such as the FlexSim, but there will also be opportunities to build custom simulations in python to address other questions. Your work in this high-pace environment will be critical in accelerating the speed of development by making the most out of available data and avoiding the construction of systems that can’t deliver the needed performance.

Key job responsibilities

• Build complex discrete event simulations to compare potential solutions and accelerate the design of integrated systems.
• Investigate the sensitivities of designs to perturbation.
• Quantify the implications of emergent data and observations.
• Explore the potential of proposed improvements and the potential impacts of other proposed changes to system design.
• Use a range of data science methodologies to conduct analysis for cases when the solution approach is unclear that relate to a portion of a business or business process.
• Apply a breadth of experience from practical application of data science techniques and tools to solve difficult business problems.
• Design and implement scalable and reliable approaches to extract the best information possible from the data.
• Make trade-offs between methods and apply best practices to validate your solutions.
• Work with business stakeholders, other scientists, and engineers to identify data requirements for a given problem.
• Use a data-driven approach to evaluate existing and new technologies required for a solution.
• Write clear and factually correct documents, including substantial data and analytical components.
• Explain technical concepts and assumptions to non-technical audiences.
• Develop metrics to quantify the benefits of a solution and influence project resources.
• Audit metric data and use it to measure project progress and success.
• Help your team and the business evolve by actively participating in discussions, team planning, office hours, and metric reviews.

About the team

Advanced Technology – Systems Engineering and Analytics (AT-SEA)

The Robotics Advanced Technology team develops and deploys products to the worldwide network with a focus on modular automated solutions in the warehouse environment. AT-SEA team members partner with our engineers to test, evaluate, and develop a wide variety of new technologies that will enhance Amazon’s ability to delight and serve our customers throughout the world. They focus on investigating upstream, downstream, and adjacent dependencies and looking critically at the reliability, quality and performance of products under development.

BASIC QUALIFICATIONS

• Master’s degree (or Bachelors degree or 5+ years of experience) in a quantitative discipline such as Statistics, Mathematics, Data Science, Business Analytics, Economics, Finance, Engineering, or Computer Science
• 2+ years of experience working as a data scientist or a similar role involving data extraction, analysis, statistical modeling, and communication
• 2+ years of experience using data querying languages (e.g. SQL, Hadoop/Hive)

PREFERRED QUALIFICATIONS

• Proficiency with FlexSIM or other discrete event simulation system
• Experience within the domain of manufacturing or logistics automation
• Able to independently own and solve a well-defined business problem where the solution has not yet been outlined or approach is unclear.
• Solutions are high quality solutions (e.g., accurate, efficient) and do not require refinement to deliver value.
• Able to solve difficult problems that require a range of data science methodologies combined with subject matter expertise.
• Understands how to gather and use complex data set across domains.
• Produces solutions that are testable and reproducible.
• Documents and share findings in line with scientific best practices for both technical and nontechnical audiences.