R&D Data Visualization Engineer

Pubblicato il 01-11-2026 · Chiesi · Roma

OverviewIn this role you will transform complex data into clear visuals that guide R&D; decisions. You will work closely with data scientists and stakeholders to design dashboards and tools that communicate insights effectively. You’ll build and maintain visualization solutions, ensure usability and reproducibility, and stay current with new techniques in pharma visualization. This position sits at the heart of Chiesi's R&D; data-driven culture, offering impact across projects and collaborations with universities and partners. Join a mission-driven environment that values reliability, transparency and continuous learning.

Retribuzione / Benefits

comprehensive healthcare programswork-life balance initiativesrelocation supportcompetitive salary with performance bonusesflexible working arrangementsremote work options

Responsabilità

Analyze large datasets to identify trends and insights for decision makingDesign and implement visual representations (charts, dashboards) to communicate findingsDevelop and maintain data visualization tools and software using Python, R, JS or platforms like Tableau/Power BICollaborate with data scientists,



analysts and stakeholders to tailor visuals to needsEnsure visualizations are user-friendly, accessible and reproducibleDocument development work for quality and knowledge sharingEngage with external partners and academics to apply modern visualization modelsPresent findings to the R&D; team and stay updated on new visualization methods

Requisiti fondamentali

Bachelor's in Data Science or Computer Science (or related field) with master's as a plusProficiency in data visualization tools (Tableau, Power BI)Programming skills in Python and/or R; knowledge of JavaScriptStrong SQL for data manipulationAbility to translate stakeholder needs into theoretical models and codeEffective communication across technical and non-technical audiencesTeam-oriented and capable of cross-functional collaborationAttention to detail and emphasis on scientific rigor and reproducibilityAdaptability and willingness to learn new technologiesstrong communicationcollaborationproblem-solvingTableauPower BIPython
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