Senior Applied Scientist, Global Reliability

Il y a 3 mois

Luxembourg Amazon EU Sarl Temps plein

MS in Data Science, Machine Learning, Statistics, Computer Science, Applied Math or equivalent highly technical field
- 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.
- Experienced in computer science fundamentals such as object-oriented design, data structures and algorithm design

As Applied Scientist in DST you will be focused on leading the design and development of innovative approaches and solutions by leading technical work supporting RME’s Predictive Maintenance (PdM) and Spare Parts (SP) programs.
You will connect with world leaders in your field and you will be tackling customer's natural language challenges by carrying out a systematic review of existing solutions. The appropriate choice of AI methods and their deployment into effective tools will be the key for the success in this role.

Key job 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

A day in the life
As Applied Scientist in DST you will be focused on leading the design and development of innovative approaches and solutions by leading technical work supporting RME’s Predictive Maintenance (PdM) and Spare Parts (SP) programs.
You will connect with world leaders in your field and you will be tackling customer's natural language challenges by carrying out a systematic review of existing solutions. The appropriate choice of AI methods and their deployment into effective tools will be the key for the success in this role.

About the team
Our mission is to leverage the use of data, science, and technology to improve the efficiency of RME maintenance activities, reduce costs, increase safety and promote sustainability while creating frictionless customer experiences.

Luxembourg, LUX
- PhD in Data Science, Machine Learning, Statistics, Computer Science, Applied Math or equivalent highly technical field
- Working experience in applied science and/or machine learning using models and methods such as neural networks, random forests, SVMs or Bayesian classification
- Experience in writing academic-styled papers for presenting both the methodologies used and results for data science projects
- Basic skills in probabilistic modeling and reliability methods

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