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Titolo:  Internship - Process Virtualization and Intelligence

Codice ID della posizione:  20862
Paese:  Milano
Funzione:  Ricerca e Sviluppo
Tipo di Contratto:  Stage
Anni di esperienza:  senza esperienza
Descrizione: 

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 3,800 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 2021.
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.

 

We are looking for a data scientist on consistent db.To manage vast amounts of inter-functional data, and help R&D dept. to make smarter strategic and technological decisions to deliver even better products and to be even more efficient. being part of a growing group of analysts dedicated to finding new inter/intra functional laws made up of ever-increasing amounts of data. applying machine learning & data mining techniques, doing statistical analysis, and building high quality systems to support the R&D processes.querying different sources of data coming from different functions, from Business Marketing until the Manufacturing and Quality, integrating all R&D organizational interfaces.

 

Focus will be in 
•    Participating and supporting the development of R&D data analytics team to create useful operative applications and reports & dashboard for the management and operative users (from the product roadmap to the shopfloor)
•    Participating and supporting the transition phase towards the PLM platform (Cloud based) taking care for the robustness of data bases both in cloud and on-premise and taking advantage of new opportunities and potential
•    Managing the functional specifications Vs internal IT Dept and external suppliers for:
•    Creating R&D applications and services based on data analisis results linked to a technological workflow

 

Responsibilities 
•    Data mining using state-of-the-art methods
•    Enhancing data collection procedures to include information that is relevant for building analytic systems
•    Processing, cleansing, and verifying the integrity of data used for analysis
•    Doing ad-hoc analysis and presenting results in a clear manner
•    Creating ad-hoc systems, including U.I., digitalizing processes and building databases.

 

Requirements: 

Qualifications
•    K-H on creation of smart application to be used in short time
•    K-H on creation of strategic reports & operative dashboards in QlikSense 
•    Knowledge of other data visualization tools, such as D3.js, plot.ly, etc. is welcome.
•    Proficiency in using query languages (SQL) on different db type (Oracle, MS SQL server) and on non relational (Mongo db)
•    Experience with common data science toolkits, such as Python and .NET/C#/VB
•    Experience with common tool in versioning as Github
•    Proficiency on MS Office pack (above all Excel, VBA for excel)

 

Skills
•    Good applied statistics skills, such as distributions, statistical testing, regression, etc.
•    Good scripting and programming skills 
•    Data-oriented personality
•    Great communication and team building skills

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