Simulation Machine Learning Analyst

Job title:

Simulation Machine Learning Analyst

Company:

RINA

Job description

RINA is currently recruiting for a Simulation Machine Learning Analyst to join its office in TURIN within the Space & Defence Division.MissionThis role is usually use for entry level (new hired people without experience and new graduates)Key AccountabilitiesGeneral purpose skills

• Good knowledge of spoken and written English. All documentation must be produced in English.
• Knowledge of Microsoft Windows 7 / 10 and Windows Server 2008 / Server 2012/ Server 2016/ Server 2019 operating systems.
• Diploma or degree, preferably in an aeronautical field.
• At least 3 years of experience in the aeronautical field.
• Basic knowledge of the principles of Human Machine Interface on PC.
• Ability to work independently within assigned roles and responsibilities.
• Knowledge of Office software for project documentation preparation (Word, Excel, etc.).

Technical skills

• Basic knowledge of mathematics and statistics.
• Knowledge of data structures and algorithms.
• Knowledge of machine learning, artificial intelligence, and deep learning / neural networks.
• Knowledge of data mining techniques.
• Knowledge of the main big data analysis techniques.
• Knowledge of data visualization and business intelligence tools.
• Programming skills in scripting languages (e.g., Python) for the implementation of stubs and demonstrative prototypes of micro-functionalities.
• Skills in identifying and implementing solutions for training (Deep) Machine Learning algorithms (to be exercised on the basis of the techniques selected for the implementation of the components).
• Skills in the definition/design of server-client configurations in a MS Windows context for the distribution of computational tasks.
• Skills in the definition and configuration of virtual machines.
• Skills in the definition, setup, and maintenance of DBMS (e.g., SQL).
• Skills in the definition of data models for DBMS adequate for the use with machine learning / big data analytics systems.
• Knowledge of avionic mission systems.
• Knowledge of ground mission support systems.

#LI-MM2EducationBachelor’s DegreeMaster’s Degree in Aerospace Engineering or Computer ScienceQualificationsCompetencies

• CLIENT INTIMACY – Embrace internal and external client needs, expectations, and requirements to ensure maximum satisfaction
• EARN TRUST – Take everyone’s opinion into account and remain open to diversity
• PROMOTE SUSTAINABLE DEVELOPMENT – Promote commitment by keeping promises as a Role Model
• MANAGE EMOTIONS – Recognise one’s and other’s emotions and express and regulate one’s reactions
• PIONEER CHANGE – Actively embrace change and benefite from the new circumstances
• BUILD NETWORK – Forge trust relationships, across departments, and outside the organization
• MAKE EFFECTIVE DECISIONS – Structure activities according to priorities, actions, resources and constraint
• ADDRESS THE WAY – Have a big picture of different situations and reinterprete it in a perspective way
• THINK FORWARD – Capitalise on experiences and translate them into action plans for the future

With over 5,600 employees and 200 offices in 70 countries worldwide, RINA is a multinational player which provides certification, marine classification, product testing, site supervision and vendor inspection, training and engineering consultancy services across a wide range of sectors. Our business model covers the full process of project development, from concept to completion. The aim is to guarantee a project’s technical, environmental and safety – and sometimes also economic and financial – sustainability.At RINA, we endeavor to create a work environment where every single person is valued and encouraged to develop new ideas. We provide equal employment opportunities and are committed to creating a workplace where everyone feels respected and safe from discrimination or harassment of any kind. We are also compliant to the Italian Law n. 68/99.

Expected salary

Location

Roma

Job date

Wed, 14 Feb 2024 06:14:00 GMT

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