Applied Data Scientist (F/M) 1

Alstom; Saint-Ouen; Sur place; EUR 45 000 - 65 000; Plein temps

Résumé du poste

A global transportation solutions company is seeking an Applied Data Scientist to develop and apply advanced maintenance algorithms. Working in a dynamic team, you will contribute to R&D and MLOps strategies. The ideal candidate has a strong background in machine learning and holds a relevant degree. Join us to tackle exciting challenges and make an impact in global mobility.

Prestations

Dynamic team environment

International projects

Commitment to diversity and inclusion

Qualifications

• Experience in machine learning, data mining, or productionalization of ML models.
• Expert knowledge of Python programming and data science frameworks.
• Knowledge of modern statistics, time series, and signal processing.

Responsabilités

• Develop feature engineering and statistical algorithms.
• Contribute to automation of the machine learning lifecycle.
• Improve the performance and scalability of solutions.

Connaissances

Programming languages (Python)

Machine learning algorithms

Data visualization

Problem solving skills

Fluent English

Formation

Engineering or master's degree

PhD in relevant fields

Outils

sklearn

PyTorch

PostgresSQL

Description du poste

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 theAdvanced 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 signalling 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 applying state‑of‑the‑art advanced maintenance algorithms for railway customers and projects around the globe. This position is open to both applied data scientists with a passion to apply state‑of‑the‑art methods and technologies to solve data science problems at scale as well as ML engineers with a strong data science background and an inclination for the productionalization of data science solutions.

Your purpose will be:

• Contribute to the R&D, development and deployment of the different machine learning, statistical and operational algorithms for the different industrialised use cases of our portfolio of services and solutions.
• Contribute to the MLOps strategy and model industrialization at scale (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 focus

REQUIERED COMPETENCES

Mandatory

Engineering or master's degree supplemented by experience in machine learning, data mining, or industry level development and productionalization of machine learning models and data science solutions.

Desirable

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 controlExperience with modern software development technologies (git, agile methodologies)
• Exposure to data engineering technologies (SQL, streaming processing concepts, data lake concepts ...) and MLOps
• 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.

WE OFFER

Be part of a dynamic team in charge of building data science and advanced analytics solutions addressing in an international company, solving the most interesting challenges for tomorrow’s mobility at global scale. We as a team deep dive into multiple machine learning and data science techniques and iterate rapidly with a focus on end-to-end, feasible and actual impact implementations. You will work inside an international team facing the challenges of real production projects.

You don’t need to be a train enthusiast to thrive with us. We guarantee that when you step onto one of our trains with your friends or family, you’ll be proud. If you’re up for the challenge, we’d love to hear from you!

Important to note

As a global business, we’re an equal‑opportunity employer that celebrates diversity across the 63 countries we operate in. We’re committed to creating an inclusive workplace for everyone.