Head Of R&D Data Elaboration
Pubblicato il 14-09-2026 - Chiesi in La Spezia
OverviewStrategic leader driving the digital transformation of R&D; through advanced data elaboration, modelling and visualization.
You will grow and mentor a team, translate research needs into data solutions, and shape the data-centric roadmap across R&D.;
Your work turns complex data into actionable insights, leveraging HPC and external partnerships.
This role strengthens Chiesi's R&D; capabilities and global collaboration.
Retribuzione / Benefitsremote work opportunities
flexible working approach
relocation support
tax assistance for foreign colleagues
people-care services
continuous training and development
ResponsabilitàLead and grow a high-performing data elaboration and visualization team
translate stakeholder needs in R&D; into data solutions aligned with research goals
drive the R&D; digital transformation by implementing the data roadmap
oversee the lifecycle of data models and visualizations from design to deployment
contribute to budget planning for data elaboration initiatives
develop advanced analytical models to enable data-driven decisions
support the R&D; data platform, including HPC-enabled analytics
establish quality standards for data elaboration and modeling
collaborate with COIC to enhance data capabilities
consolidate the digital network with internal and external partners
support cross-functional corporate data initiatives impacting R&D;
forge and manage strategic partnerships with external orgs and academia
communicate findings to R&D; leadership through clear reports
stay updated on latest data visualization and analytics trends
champion adoption of new technologies in R&D;
enhance Chiesi's reputation as leader in analytics and tech
participate in AI governance as part of the R&D; Vertical Committee and R&D; Squad
Requisiti fondamentaliPhD or Master's in relevant field
minimum 5+ years leading data elaboration/computation modelling in pharma/biotech/medtech
strong communication to both technical and non-technical audiences
team-oriented and cross-functional collaboration
attention to detail and scientific rigor
data visualization tools (Tableau, Power BI)
programming languages (Python, R, JavaScript)
data manipulation (SQL)