Machine Learning Officer - Senior

Open 55d

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:

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:

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:

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

See also