{"id":2950906,"url":"https://alion.io/job/pirelli-internship-material-process-technologist","title":"Internship Material Process Technologist","company":{"id":451165,"name":"Pirelli","domain":"pirelli.com","url":"https://alion.io/company/pirelli-2","size_band":"1001-5000","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"SuccessFactors","truth_index":{"grade":"B","score":79,"open_postings":28,"ghost_share":0,"stale_share":0.857,"repost_share":0,"time_to_fill_p50_days":43,"computed_at":"2026-10-27T05:46:45Z"}},"role":"Early Careers","role_family":"Early Careers","seniority":"intern","employment_type":"internship","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Milan, Italy"],"countries":["IT"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":18500,"max_usd":36000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":8},"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Python","optional":false},{"name":"SQL","optional":false},{"name":"Git","optional":true},{"name":"NumPy","optional":true},{"name":"Pandas","optional":true},{"name":"Plotly","optional":true},{"name":"QlikSense","optional":true},{"name":"Scikit-learn","optional":true}],"status":"live","first_seen_at":"2026-10-20T19:58:40Z","employer_posted_date":"2026-10-20","last_verified_at":"2026-10-27T09:29:13Z","board_verified":true,"closed_at":null,"days_open":6,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":6},"description":"Material process data technologist - Internship\nDRIVE YOUR FUTURE\nYou will join the Material virtualization group in the R&D Materials and Innovation area.\nMaterial process data technologist, in strong collaboration with materials scientists, compounders, process engineers, data scientists, and digital development teams will translate laboratory, formulation, characterization, and manufacturing data into meaningful insights. The role will help accelerate material development, deepen structure-property-process understanding, and support data-driven decisions across Materials R&D.\nWHAT YOU WILL LEARN\nYou will collaborate with your tutor in:\n· Collect, organize, and analyze data from laboratory activities, material characterization, and manufacturing processes.\n· Work with materials experts to define technically meaningful descriptors, test parameters, data hierarchies, and metadata for polymers, elastomers, fillers, additives, rubber compounds, and related material systems.\n· Identify, query, and integrate data from multiple databases and digital sources to support R&D projects.\n· Evaluate data quality, consistency, and reliability, collaborating with stakeholders to improve data governance and usability.\n· Apply statistical methods, data analytics techniques to identify trends, relationships, and opportunities for process and material optimization.\n· Develop scripts, dashboards, and analytical tools that enable materials researchers and engineers to compare formulations, explore characterization results, identify trends, and support experimental planning.\n· Collaborate with data scientists and software developers to industrialize analytical workflows and deploy data-driven solutions.\n· Support the definition of data models and data collection strategies for industrial digitalization initiatives.\n· Contribute to the documentation of methodologies, analytical workflows, and best practices.\n· Promote a materials-informed, data-driven culture within the Materials R&D organization.\nWHAT WE ARE LOOKING FOR\n· Master's degree in STEM area.\n· Familiarity with data visualization, exploratory data analysis, and statistical methods applied to scientific or engineering datasets.\n· Programming skills in Python and knowledge of SQL and database querying.\n· Strong problem-solving, scientific reasoning, and analytical thinking skills.\n· Fluency in English.\nPREFERRED QUALIFICATIONS\n· Understanding of materials science, polymers, elastomers, rubber compounds, or manufacturing processes.\n· Design of experiments and cheminformatics\n· Familiarity with scientific Python ecosystem (e.g., Pandas, NumPy, Scikit-learn, Plotly).\n· Knowledge of data visualization platforms such as Qlik Sense.\n· Basic understanding of software development practices (Git, APIs, version control).\n· Exposure to web technologies or frontend development.\nAPPLY NOW, DRIVE YOUR FUTURE","description_format":"text","description_chars":2882,"description_truncated":false,"requirements":{"experience_years_min":null,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":{"level":"master","optional":false},"security_clearance":false,"languages":[{"language":"English","level":"Advanced (C1)","optional":false}]},"benefits":[],"hiring_locations":[],"hiring_excludes":[],"relocation_offered":false,"industries":["Automotive 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