Leading societies to a low carbon future, and acknowledging the current transformative power of AI, Alstom develops and markets mobility solutions that provide the sustainable foundations for the future of transportation. Our product portfolio ranges from high-speed trains, metros, monorail, and trams to integrated systems, customised services, infrastructure, signalling and digital mobility solutions. Joining us means joining a caring, responsible, and innovative company where more than 70,000 people lead the way to greener and smarter mobility, worldwide.


Join us as an Applied Data Scientist in the Advanced Maintenance Analytics team based in Saint Ouen, France.


As a part of its predictive maintenance solutions, Alstom Services Advanced Maintenance Analytics aims to offer tools and enhance state-of-the start specific solutions to manage the health of rolling stock and signaling equipment to detect, prevent and forecast degradation and provide diagnosis to maintenance teams at fleet scale.


PURPOSE

You will be a core member of the machine learning team dedicated to developing and apply state-of-the-art advanced maintenance algorithms for railway customers and projects around the globe.

Your purpose will be:

Contribute to the R&D and deployment of the different machine learning, statistical and operational algorithms for the different industrialized use cases of our portfolio of services and solutions.
Contribute to the MLOps strategy (CI/CD of developed models, model monitoring, data labelling, training and improvement, etc..)
Be a proactive member in the choice and applied research of different machine learning, statistical and data mining approaches

MAIN RESPONSIBILITIES

Develop feature engineering, machine learning and statistical algorithms and models.
Continuously improve the performance and scalability of our solution
Contribute to the automation of the full machine learning development lifecycle: scoping, development, training, validation, deployment, monitoring and productionalization
Bring new state-of-the-art algorithms with an applied and solution oriented

PhD in the fields of physics, engineering, statistics, computer science or related disciplines

EXPERIENCE

Mandatory:

Expert knowledge of programming languages like Python and popular data science programming framework and tools (sklearn, PyTorch, etc..)
Knowledge of fundamentals of modern statistics, including time series, signal processing, and text mining
Experience with machine learning algorithms tuning and validation
Data visualization (Python modern frameworks)
Experience with database management (PostgresSQL, noSQL, etc.)
Experience with LINUX environment (shell scripting) and modern development stack

Desirable:

Experience with predictive maintenance applications
Knowledge of MLOps tools (mlflow, etc.) and data version control
Experience with modern software development technologies (git, agile methodologies)
Exposoure to data engineering technologies (SQL, streaming processing concepts, data lake concepts ...)
Experience working with cloud providers like Microsoft Azure, AWS or GCP
Knowledge of docker, kubernetes and CI/CD stack


SKILLS

Technical person, problem solver with good communication skills
Proven track record for designing stable solution, testing and debugging
Demonstrated teamwork and collaboration in a professional setting
Fluent English. French is a plus.