Machine Learning (M/F)

Claire Joster is looking for a Machine Learning (M/F). Our client operates in the area of ​information technology services.

Role:

Analyze internal clients’ needs:

– Collaborate with clients to best understand their operational and strategic needs in terms of complex AI/ML challenges;

– Investigate and solve business issues using technical, data-driven, AI/ML strategies;

-Build and/or adapt AI/ML models:

– Design and develop Machine Learning (ML) and Artificial Intelligence (AI) solutions, i.e., collect labeled data, setup and train models, test and evaluate results;

– Work closely with clients during application roll-out and all stages of the application lifecycle;

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

–Implement and assist the deployment and maintenance of models:

– Follow to best practices in the industry 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.

Requirements:

– Up to 2 year experience as Data Analyst / Data Scientist / Machine Learning Specialist in at least one of the following areas:

– NLP, data extraction, document processing or process automation projects;

– Classification / Regression / Clustering Machine Learning and/or statistical models;

– Deep Learning models preferentially in the context of NLP, Speech-to-text or computer vision projects ;

– Artificial Intelligence techniques and paradigms;

– Exposure to professional software development environment.

SKILLS:

– Fluent in English (C1- C2);

– High statistical and quantitative analysis skills (e.g. machine learning models, statistical models, Bayesian statistics, probability theory, time series analysis, …);

– Knowledge of ETL methods;

– Knowledge of Machine Learning models;

– Knowledge of NLP and/or computer vision techniques;

– Knowledge of deep learning architectures and frameworks (e.g. TensorFlow, Keras, …);

– Knowledge of at least one ML development stack (e.g. Scikit-learn, Keras, PyTorch…);

– Effective Programming skills (e.g. Python) and algorithmic knowledge.