Data Analytics & Automation Intern

Bridgestone Europe NV/SA; Roma; On-site; EUR 6,700 - 10,000; Full time

Job summary

Bridgestone Europe NV/SA in Rome is seeking an intern for the Operational & Strategic Excellence team to support the digital transformation of raw material sourcing. You will learn data consolidation, data quality checks and process automation using Python and Excel, with guidance from a company tutor and team.

The internship offers hands-on exposure to procurement analytics, data harmonization and reporting.

Qualifications

• Master’s degree in Data Science, Data Analytics, Computer Science, Engineering, Statistics, Economics, Business Analytics or a related field.
• Analytical education and understanding of business processes is considered an advantage.

Responsibilities

• Learn data preparation, validation, analysis and basic automation in a business context.
• Understand main steps in raw material sourcing and supplier quotation analysis.
• Translate business needs into structured data requirements for supervised analytics.
• Strengthen documentation, communication, teamwork and responsible data handling.
• Contribute to data structure definition, validation rules and quality checks.
• Support automation or semi-automation activities related to reporting.

Skills

Python

SQL

Excel

Pandas

NumPy

Data visualization

Automation

Data quality

Education

Master’s degree in Data Science or related

Tools

Jupyter/Notebooks

Cloud platforms

Job description

Requisition ID55818-Posted23/10/2026-IT-TCE-ROMA (IT-ITCC)- Country (1) - Job Family (1) -Full time-Open-ended/permanent

We are looking for a motivated intern to join the Operational & Strategic Excellence team for a structured learning experience focused on the digital transformation of raw material sourcing activities. With guidance from the company tutor and team members, the intern will develop practical skills in data consolidation, data quality and process automation, working with supplier quotation information exchanged through emails and Excel files.

The internship offers supervised exposure to a real business challenge at the intersection of procurement, data analytics and automation. Through coaching, observation and gradual participation in project activities, the intern will learn how structured and reliable data can support more efficient, consistent and transparent sourcing decisions.

Raw material sourcing processes involve multiple quotation rounds, numerous supplier inputs and information that needs to be compared and consolidated. Part of this activity creates a useful learning environment in which the intern can understand data preparation, harmonization and reporting practices.

The Operational & Strategic Excellence team is supporting the development of automated or semi-automated processes for business intelligence reporting. Under supervision, the intern will learn how these reports support the evaluation of supplier quotations and target price adjustments during sourcing activities.

The purpose of the internship is to develop the intern's professional and technical skills through supervised participation in activities related to sourcing data and reporting. The learning path will include understanding the current process, structuring data from different sources, recognizing data quality issues, and contributing to analytical or automation solutions. Activities will be assigned progressively and carried out with guidance from the company tutor and relevant team members.

Responsibilities

• Learn how raw material quotation data flows across sourcing rounds, emails, spreadsheets and other available sources.


• Support the collection, organization, cleaning and standardization of supplier quotation data to develop data preparation skills.


• Contribute to the definition of common data structures, validation rules and quality checks, with coaching from experienced colleagues.


• Practice the use of Python and Excel by supporting the improvement of tools for data matching, consolidation, transformation and analysis.


• Participate in supervised automation or semi-automation activities related to matrix preparation and recurring reporting.


• Support the comparison of supplier quotations and preparation of analytical outputs, while learning how they are used in sourcing decisions.


• Learn to identify data gaps, inconsistencies, duplicates and process bottlenecks, and discuss possible improvements with the tutor and team.


• Contribute to documenting data logic, process steps, assumptions and user guidance to support repeatability and knowledge sharing.


• Work alongside Category Managers, procurement colleagues and other stakeholders to understand requirements and participate in solution testing.


• Prepare and present findings and learning progress with support from the company tutor, adapting communication to technical and business audiences.

Qualifications & Experience Required

Education, Master, other certification:

• Master’s degree in Data Science, Data Analytics, Computer Science, Engineering, Statistics, Economics, Business Analytics or a related field.


• A combination of analytical education and an understanding of business processes is considered an advantage.

Experience (years):

0+ years

Technical Skills

• Good working knowledge of Python for data preparation, analysis and automation.


• Knowledge of SQL and relational data concepts.


• Strong Microsoft Excel skills, including data cleaning, formulas, lookups, pivot tables and structured datasets.


• Familiarity with data manipulation libraries such as Pandas and NumPy is preferred.


• Understanding of exploratory data analysis, data validation and data quality principles.


• Experience with data visualization or reporting tools is an advantage.


• Exposure to cloud platforms, notebooks, large-scale data tools or process automation is welcome but not mandatory.


• Interest in procurement, sourcing processes and digital transformation. Previous procurement experience is not required.

Languages Skills:

• Good written and spoken English.


• Additional languages are considered an advantage.

Soft/Behavioral Skills:

• Analytical and structured approach, with strong attention to detail.


• Curiosity and willingness to understand both the data and the business process behind it.


• Practical problem-solving mindset and ability to convert requirements into workable solutions.


• Ability to organize assigned learning activities, ask for guidance when needed and collaborate effectively in a cross-functional and international environment.


• Clear communication skills and willingness to develop confidence in explaining analytical topics to non-technical stakeholders.


• Proactive learning attitude, reliability and openness to feedback, testing and iteration.


• Strong respect for data confidentiality, accuracy and responsible information handling.

Learning Objectives and Tutoring

The internship will be supported by a formal learning plan and will focus on the progressive development of technical, analytical and professional skills.

• Develop practical knowledge of data preparation, validation, analysis and basic automation in a business context.


• Understand the main steps and stakeholders involved in raw material sourcing and supplier quotation analysis.


• Learn how to translate business needs into structured data requirements and supervised analytical activities.


• Strengthen documentation, communication, teamwork and responsible data-handling skills.

The company tutor will guide the learning journey, provide regular coaching and feedback, supervise assigned activities, and support the operational steps required for the activation and execution of the internship. The intern will participate in projects as a learner and contributor, without autonomous ownership of business deliverables.