Job description

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.

At Pirelli you will apply statistical analysis and machine-learning techniques on a wide range of data (from sensors, to telemetry to manufacturing) and you will change how decisions are made across all business units.

You will be in charge of coming up with effective and scalable solutions that, leveraging internal and external data, will answer questions such as for example:

1. “How can we optimize our supply chain flow in a particular geographic region?”

2. “How can we build an effective and scalable real time monitoring system for production quality control?”

3. “How can we parse and model IoT data to derive crucial insights and deliver impactful results?”

4. How to improve business-to-consumer services with data-driven solutions?

5. How to drive new product development?

6. How to design personalized campaign based on consumer behavior?


  • Translate business questions to data science problems
  • Develop, tune and deploy custom, scalable, predictive models
  • Support implementation of data pipelines considering data products requirements
  • Present complex concepts to a non-technical stakeholders in a simple manner
  • Manage a data science product end-to-end from concept to production
Data Management

Data Science and Analytics

Required Skills:
  • A passion and curiosity for data and data-driven decision making
  • Broad knowledge of statistical learning
  • Deep knowledge of applied statistics including multivariate statistical analysis, Bayesian statistics, Time Series analysis
  • Extensive experience in machine learning models development and deployment
  • Ability to effectively communicate findings and rationale behind predictive models implemented to executives and management
  • Ability to prototype and test suboptimal solutions quickly and iterate up to a final product that can be deployed in production
  • Advanced knowledge of Python and related scientific libraries (pandas, scipy, numpy, jupyter)
  • Extensive knowledge of scikit-learn, statsmodels and related machine learning/stats/data mining packages
  • Experience with GIT, CI is a must
  • Advanced knowledge of SQL
  • Ability to communicate and collaborate with other team members
  • Prior experience using agile and scrum
Desired Skills:
  • Knowledge of deep learning
  • Experience with tensorflow
  • Experience in Apache Spark
  • Working experience with AWS cloud framework and services
  • Experience with Docker
Is considered a plus:
  • Create visualization and interactive dashboards to communicate results of analysis and outcome of models in a meaningful and actionable manner
  • Previous experience in professional end-to-end deep learning projects using TensorFlow
English (mandatory) / Italian (nice to have)

Master in Computer Science, Physics, Math, Engineering, Statistics or any other data-oriented disciplines.

PhD is a plus.

At least 3 years of experience in a data science position

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