About the Company

Inetum is a European leader in digital services. Inetum’s team of 28,000 consultants and specialists strive every day to make a digital impact for businesses, public sector entities and society. Inetum’s solutions aim at contributing to its clients’ performance and innovation as well as the common good. Present in 19 countries with a dense network of sites, Inetum partners with major software publishers to meet the challenges of digital transformation with proximity and flexibility. Driven by its ambition for growth and scale, Inetum generated sales of 2.5 billion euros in 2023.

About the Role

Develop End to End Product Lifecycle:

• Develop Machine Learning (ML) and Artificial Intelligence (AI) solutions i.e., collect and label data, setup and train models, test and evaluate results

• Develop, modify, and support in-house applications, working hand-in-hand with the data scientists and developers of the AC team

• Work closely with clients during all stages of the application life cycle

• Design the most adequate approaches to solve the identified problems within the company’s framework

Implement and assist the deployment and maintenance of models and software:

• Follow industry best practices to implement and scale out the developed solutions into production grade software

• Assist the operational teams with the deployment, monitoring and maintenance of the developed solutions

• Contribute to disseminate a culture of data driven solutions within CIB

• Maintain a strong market watch on the latest developments on methodologies, technologies, and tools"

Main Tasks:

• Develop End to End Product Lifecycle

• Implement and assist the deployment and maintenance of models and software

Technical Skills:

• Ability to explain the results of a model and the different elements impacting it

• Statistical and quantitative analysis skills (e.g., machine learning models, statistical models, Bayesian statistics, probability theory, time series analysis,

• Knowledge of at least one ML development stack (e.g. scikit-learn, keras, …)

• Knowledge of NLP techniques

• Effective Programming skills (e.g., Python, R, Java, Go) and algorithmic knowledge.

• Knowledge of databases and associated tools (SQL and No SQL)

• Familiarity with continuous integration tools (pref. Jenkins, Git)

• Knowledge of deep learning architectures and frameworks (e.g., Py Torch, Tensor Flow,…)

Language Skills:

• Fluent English

• French and Portuguese are a plus

Soft Skills:

• Ability to think abstractly and creatively

• Excellent communication and interpersonal skills

• Flexibility: ability to work in a changing environment

Education

• Engineer School/master’s degree from university with a specialization in mathematics, statistics, computer science, data science or any engineering related field

• Although not strictly required a Ph D on data-science, engineering or related fields is an advantage