Head of R&D Data Elaboration

This is what you will do

The R&D Data Elaboration Head is a strategic leadership role responsible for championing and leading the digital transformation of R&D through computational modelling, data elaboration and visualization that directly supports R&D activities and product development lifecycle. His/Her team will be crucial in transforming complex data into actionable insights, leveraging both our internal architectural capabilities and external partnerships.

You will be responsible for

• Lead and grow a high-performing team dedicated to data elaboration and visualization, fostering a culture of innovation and excellence.
• Translate stakeholder needs within R&D into effective data elaboration and visualization solutions, ensuring alignment with research and development goals.
• Drive the digital transformation of R&D by contributing to and implementing the digital roadmap, with a strong focus on data-driven approaches.
• Oversee the entire lifecycle of data models and visualizations for R&D, from design and development to deployment and ongoing optimization.
• Contribute to budget planning and priority setting for R&D's data elaboration initiatives, ensuring resources are allocated effectively.
• Develop and implement advanced analytical models that empower R&D to make data-driven decisions and foster a truly data-centric organization.
• Support the definition and management the R&D data elaboration platform, including leveraging High-Performance Computing (HPC) solutions to meet demanding analytical needs.
• Establish and enforce robust quality standards for all data elaboration and modeling activities, ensuring accuracy, reliability, and reproducibility.
• Collaborate with the Center of Innovation and Competence (COIC) to identify and implement initiatives that enhance data elaboration and visualization capabilities across the organization.
• Consolidate the digital network with internal experts and partners (Global ICT, Legal, R&D Procurement, Transformation Office, R&D functions). Support R&D in any Corporate wide data initiatives aimed at transforming the way Chiesi is generating, collaborating, acquiring, managing, models across the company.
• Forge and manage strategic partnerships with external organizations, universities, and consortia to integrate state-of-the-art models and methodologies.
• Effectively communicate complex findings and insights to the broader R&D team and leadership through clear, concise reports and presentations.
• Stay at the forefront of innovation by continuously monitoring and evaluating the latest advancements in data visualization techniques, analytical methodologies, and pharmaceutical research trends.
• Champion the dissemination and adoption of emerging technologies and novel product/process design methods within R&D.
• Enhance the company's international reputation as a leader in process/product development, advanced analytics, and innovative technologies.
• Chiesi digital governance: be the R&D member of “AI” Vertical Committee and active participant of R&D Squad.

You will need to have

• PhD or Master's degree in Data Science, Computer Science, Statistics, or a related field.

• Minimum of 5+ years of leading in data elaboration/computation modelling in pharmaceutical/biotech/medtech industry

We would prefer for you to have

• In-depth knowledge of the development techniques of the main pharmaceutical platforms and forms
• Good knowledge of the drug development process
• Good knowledge of relevant regulatory requirements (GMP, FDA, ICH, EMEA, etc. guidelines)

• Good knowledge on mathematical models and advanced analytics
• Experience with data visualization tools.

• Good knowledge of the characterization parameters relevant for the different pharmaceutical forms with particular reference to inhalation ones
• Good knowledge of basic statistics
• Knowledge of the main simulation and modeling techniques used in R&D process, plant or product design
• Knowledge of the main techniques of statistical analysis on data sets and related numerical calculation methods
• Knowledge of data science, with reference to big data management and deep learning/machine learning
• Knowledge of the main analytical techniques in the characterization of pharmaceutical products in development
• Knowledge of the main Industry 4.0 technologies
• Knowledge of basic data management

• Strong ability to understand the need and to translate it into theoretical equations and code
• Strong communication skills for both technical and non-technical audiences.
• Team-oriented with the ability to work in cross-functional environments.
• Attention to detail and commitment to scientific rigor and reproducibility.
• Adaptability and willingness to learn new technologies and methods.
• Ability to work in complex networks
• Ability to support R&D strategy with data science models and visualization

• Strong skills in data visualization tools (e.g., Tableau, Power BI), programming languages (e.g., Python, R, JavaScript), and data manipulation (e.g., SQL).

Location

Location is flexible, with remote working opportunities available across Europe