Data Analytics

Vedi l’offerta su Go Lavoro: golavoro.it/annuncio-lavoro/8nb1i6

Requisition ID55818-Posted23/10/2026-IT-TCE-ROMA (IT-ITCC)- Country (1) - Job Family (1) -Tempo pieno-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 Skill

Vedi l’offerta su Go Lavoro: golavoro.it/annuncio-lavoro/8nb1i6