Titolo: R&D Data Analytics (plant Settimo Torinese)
R&D Data Analytics (plant Settimo Torinese)
Company Profile
Established in 1872, Pirelli is among the world’s leading tyre producers. It is the only pure consumer tyre company that includes car, motorbike, and bicycle tyres as well as associated services.
Pirelli has a distinct positioning in high value tyres, characterised by an advanced technology with more than 3,600 homologations obtained, thanks to partnerships with the most prestigious car manufacturers in the world. In order to achieve the highest levels of performance, safety and containment of environmental impact, Pirelli has always been strongly committed to research and development, in which it invested 6% of revenue from high-value products in 2020.
Involved in motorsport since 1907, Pirelli has been the exclusive official tyre partner of the Formula 1™ World Championship since 2011 and has renewed the agreement until 2024.
Pirelli's commitment to the creation of sustainable value, a characteristic of the Company's responsible management and its economic, social and environmental performances has resulted in its inclusion in some of the world’s most prestigious sustainability stock market indices such as the Dow Jones World and Europe Sustainability Indices and Global Compact LEAD of the United Nations.
Main Activities:
Il candidato sarà inserito nel dipartimento R&D dello stabilimento di Settimo Torinese e si focalizzerà su schematiche semplici ed efficaci nelle analisi dell uniformità e disuniformità dello pneumatico. Il lavoro è basato su analisi dati con forte utilizzo di strumenti di data anlytics e reti neurali. Oltre a questo, le stesse tecniche verranno utilizzate per sviluppare tool di analisi ad hoc su altre performance misurate in indoor, quali impronte, trazioni statiche e sezioni.
Requirments:
- Laurea Magistrale
- Ingegneria Meccanica, Laurea Matematica, Fisica
- Inglese
- Office, Database, MatLab o strumenti simili, Preparazione in data analytics
- Profilo dinamico, con propensione ad attività sul campo in realtà manufacturing. Python nice to have
- Precedente esperienza in ambito aziendale (es. stage curriculare)