Head of R&D Data Elaboration

Overview

Strategic 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 / Benefits

remote work opportunities

flexible working approach

relocation support

tax assistance for foreign colleagues

people-care services

continuous training and development

Responsabilità

Lead 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 fondamentali

Ph

D 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, Java

Script)

data manipulation (SQL)