Machine Learning Officer - Senior

Job description:

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

Language Skills:

• Fluent English

• French and Portuguese are a plus
• Effective Programming skills (e.g., Python, R, Java, Go) and algorithmic knowledge.
• Knowledge of databases and associated tools (SQL and NoSQL)
• Familiarity with continuous integration tools (pref. Jenkins, Git)
• Knowledge of deep learning architectures and frameworks (e.g., PyTorch, TensorFlow,…)

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 PhD on data-science, engineering or related fields is an advantage