Are you a talented and inventive scientist with strong passion about Artificial Intelligence and Predictive Modeling? Would you like to develop Machine-Learning models by playing a key role within EU RME Predictive Analytics team? Our mission is to drive the Predictive Maintenance (PdM) and Spare Parts (SP) programs for Amazon EU Operations that consists of complex automation, sortation, robotic and materials handling systems.
As Machine Learning Scientist you will be working with large distributed systems of data and providing predictive maintenance expertise for over 2000 maintenance engineers, managers and administrators by supporting the entire network managed by EU RME, which may include non-EU locations (such as Singapore, Australia and Japan). You will connect with world leaders in your field and you will be tackling ML challenges by carrying out a systematic literature review of Machine Learning methods applied to PdM. The appropriate choice of the ML methods and their implementation will be the key for the success of the PdM and Spare Parts programs.
This role requires an individual with strong skills in the area of data science, Machine Learning and statistics. The successful candidate will be a self-starter comfortable with ambiguity, with strong attention to detail and outstanding ability in balancing technical leadership with strong business judgment to make the right decisions about model and method choices.
Key Areas of Responsibilities:
· Provide technical expertise to support team strategies that will take EU RME towards World Class predictive maintenance practices and processes, driving better equipment up-time and lower repair costs with optimized spare parts inventory and placement
· Implement an advanced maintenance framework utilizing Machine Learning technologies to drive equipment performance leading to reduced unplanned downtime
· Provide technical expertise to support the development of long-term spares management strategies that will ensure spares availability at an optimal level for local sites and reduce the cost of spares
· Facilitate the access to data and tools for the larger Reliability Engineering team to drive reliability insights
· MS in Data Science, Machine Learning, Statistics, Computer Science, Applied Math or equivalent highly technical field
· 3+ years of hands-on experience working in data science and/or machine learning using models and methods such as neural networks, random forests, SVMs or Bayesian classification
· Proficient using R, Python, or other equivalent statistics and machine learning tools
· Experience with MySQL/PostgreSQL/Redshift
· Knowledge of AWS Infrastructure
· Strong interpersonal and communication skills. Must be able to explain technical concepts and analysis implications clearly to a wide audience, including senior executives, and be able to translate business objectives into action
· Proven ability to implement and operate at large scale
· Experienced in computer science fundamentals such as object-oriented design, data structures and algorithm design
· PhD in Data Science, Machine Learning, Statistics, Computer Science, Applied Math or equivalent highly technical field
· Experienced in writing academic-styled papers for presenting both the methodologies used and results for data science projects
· Experience in Predictive Maintenance
· Basic skills in probabilistic modeling and reliability methods