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Machine learning engineer and data scientist

Castel d'Azzano
Contratto a tempo indeterminato
SATE Systems and Advanced Technologies Engineering
Data scientist
Pubblicato il 1 aprile
Descrizione

Background: Master's degree in Computer Science, Data Science, Physics, Mathematics, or related Engineering fields with up to 5 years of experience.Activity: You will be part of a multi-disciplinary team that implements innovative AI-based and model-based software solutions for systems health monitoring, diagnostics and data mining for space and/or automotive applications. You will be supported by our team leaders in a professional growth and training path that will gradually lead you to autonomy in data analysis activities and development of models, methods and software solutions.Requirements:Excellent knowledge of advanced techniques of timeseries data analysis and modelling, including signal processing, feature extraction, Machine Learning and Deep learning applied to timeseries.Excellent knowledge of programming in high-level languages (e.G. MATLAB / SIMULINK, Python, C ++, Java); Knowledge of data mining and data cleaning techniques.Knowledge of the English language (read, written and spoken); at least level B2 (CEFR) is requiredAdvanced knowledge of the Microsoft Office environment, in particular Word and Excel.What we offer:· Hiring contract framed according to CCNL trade sector SME. · Hybrid remote working options (combination of in-office and work from home) · Opportunity to work with cutting-edge technologies, innovative technology projects and software tools development· Possibility to be involved in different projects and different fields· On-the-job training· Direct contact with innovation centers of clients and partners · Opportunities to grow in role and responsibilities · Company benefits like flexible hours, meal vouchers, online or in-company learning courses, periodical showcases and knowledge sharing sessions, common break/snack room· Salary and additional benefit/bonus commensurate with experience, autonomy and objectives achieved Work Schedule: full time, Monday through Friday, flexible hours.

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