R&D Data Visualization Engineer
Chiesi
Overview
In 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 programs
- work-life balance initiatives
- relocation support
- competitive salary with performance bonuses
- flexible working arrangements
- remote work options
Responsabilità
- Analyze large datasets to identify trends and insights for decision making
- Design and implement visual representations (charts, dashboards) to communicate findings
- Develop and maintain data visualization tools and software using Python, R, JS or platforms like Tableau/Power BI
- Collaborate with data scientists, analysts and stakeholders to tailor visuals to needs
- Ensure visualizations are user-friendly, accessible and reproducible
- Document development work for quality and knowledge sharing
- Engage with external partners and academics to apply modern visualization models
- Present 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 plus
- Proficiency in data visualization tools (Tableau, Power BI)
- Programming skills in Python and/or R; knowledge of JavaScript
- Strong SQL for data manipulation
- Ability to translate stakeholder needs into theoretical models and code
- Effective communication across technical and non-technical audiences
- Team-oriented and capable of cross-functional collaboration
- Attention to detail and emphasis on scientific rigor and reproducibility
- Adaptability and willingness to learn new technologies
- strong communication
- collaboration
- problem-solving
- Tableau
- Power BI
- Python
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