Senior Data Scientist

Job description

About us Chiesi is an international research-focused biopharmaceutical group with 90 years’ experience, operating in more than 30 countries, with its Headquarter in Parma, Italy. More than 8,000 employees across the group are united by a singular purpose: promoting a healthier world for our people, patients, and the planet. This is what drives us as we research, develop, and market innovative drugs across our main therapeutic areas. Discover more here. At Chiesi we are thinking generations ahead, driving sustainable innovation with purpose. This fosters a culture of reliability, transparency, and ethical behaviour at every level. As a Benefit Corporation and a certified B Corp, we have embedded sustainability in our bylaws and continuously measure our impact. Diversity and inclusion are at the heart of who we are. We believe our differences make us stronger. We are a vibrant ecosystem of passionate, talented individuals united by strong values, each bringing unique perspectives that help us to continuously challenge the status quo for the better. Chiesi Research & Development Our R&D team represents a fundamental asset for the business. It is divided into integrated functional areas focusing on pipeline projects including discovery and preclinical research, global technical development, drug delivery technology, clinical development, regulatory affairs, pharmacovigilance, intellectual property, quality assurance, R&D project and portfolio management. Headquartered in the new purpose-built and fully integrated Research and Development Centre in Parma (Italy), the team also has important operations in Paris (France), Chippenham (UK), Cary (US), Stockholm (Sweden), Toronto (Canada) and Shanghai (China). Who we are looking for This is what you will do The Data Scientist is responsible for designing, developing, and deploying advanced Data Science, Artificial Intelligence (AI), Machine Learning (ML), and Generative AI solutions to support Clinical Development across the drug development lifecycle. The role combines strong expertise in data science with a solid understanding of clinical research and drug development. Working with clinical trial data, real-world data, digital health technologies, Data Scientist will generate actionable insights that improve decision-making, increase operational efficiency, accelerate evidence generation, and enhance patient-centric approaches to clinical research. As part of a multidisciplinary environment, the individual will collaborate closely with Global Clinical Development teams, and Digital teams to identify opportunities where data science can create measurable impact throughout the clinical development continuum. You will be responsible for Data Science and AI Solutions for Clinical Development • Design, develop, validate, and deploy advanced analytics, machine learning, artificial intelligence, and Generative AI solutions addressing scientific, clinical, and operational challenges across Clinical Development and Clinical Operations. • Apply statistical modelling, predictive analytics, AI, and data science methodologies to generate insights from diverse healthcare and clinical data sources. • Transform complex clinical and operational data into actionable recommendations that support evidence-based decision-making. • Leverage clinical trial data, real-world data, digital health data to improve the quality, efficiency, and effectiveness of clinical development activities. • Evaluate emerging technologies, data sources, and analytical methodologies that can enhance clinical research and patient outcomes. • Ensure developed solutions are scientifically robust, reproducible, scalable, and compliant with regulatory, privacy, and governance requirements. • Contribute to the definition of data science best practices, standards, and analytical frameworks within the organization. Examples of potential application areas include: • Clinical trial design and protocol optimization. • Real World Data (RWD) and Real World Evidence (RWE) analytics. • Synthetic control arms and virtual patient cohorts. • Predictive analytics for trial performance assessment and monitoring. • Risk identification and study performance forecast. • Development and validation of digital biomarkers. • AI and Generative AI applications supporting clinical research, risk assessment and decision-making. Strategic Collaboration and Stakeholder Engagement • Partner closely with Global Clinical Development and Digital teams. • Translate scientific, clinical, operational, and business challenges into robust analytical solutions. • Facilitate the adoption and implementation of advanced analytics and AI solutions across clinical functions. • Present complex analytical findings clearly and effectively to both technical and non-technical stakeholders. • Support strategic decisions through data-driven insights and evidence generation. • Act as a trusted advisor on data science, artificial intelligence, and advanced analytics opportunities within Clinical Development. Innovation and External Collaboration • Monitor scientific and technological advancements in AI, machine learning, digital health, clinical data science, and related fields. • Collaborate with academic institutions, technology providers, CROs, healthcare organizations, and industry consortia. • Contribute to innovation initiatives aimed at transforming clinical development through data-driven methodologies. • Evaluate external technologies, platforms, and partnerships that can accelerate capability development. • Participate in scientific publications, conference presentations, and external collaborations when appropriate. • Foster a culture of innovation, continuous learning, and scientific excellence. You will need to have Technical Skills • Strong knowledge of machine learning, artificial intelligence, predictive analytics, and statistical modelling techniques. • Proficiency in programming languages commonly used in data science (e.g., Python, R). • Experience with data manipulation and analysis libraries (e.g., pandas, NumPy, scikit-learn, TensorFlow, PyTorch). • Experience developing and deploying machine learning models in production environments. • Knowledge of Generative AI technologies, Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and emerging AI frameworks. • Experience with healthcare, clinical, and real-world data sources. • Strong data visualization, communication, and storytelling capabilities. • Understanding of software development best practices, version control, and reproducible analytical workflows. Domain Knowledge Required • Demonstrated experience in Clinical Development, Clinical Research, Real World Evidence or related healthcare research environments. • Strong understanding of the clinical trial lifecycle, including study design, site activation, patient recruitment, study conduct, analysis, and evidence generation. • Experience in applying advanced analytics, AI, or machine learning techniques to clinical or healthcare datasets. Qualifications • Master's Degree or PhD in Data Science, Statistics, Physics, Computer Science, Mathematics or a related discipline. • Proven experience as a Data Scientist or equivalent role within the pharmaceutical, biotechnology, CRO, healthcare technology, or life sciences sectors. • Demonstrated experience supporting Clinical Development, Clinical Operations, Real World Evidence, or related clinical research activities. • Experience working with clinical trial data and healthcare datasets. • Proven ability to translate complex scientific and operational challenges into impactful analytical solutions. The ideal candidate The ideal candidate combines strong data science and AI expertise with practical experience in clinical development and clinical research. They are passionate about applying innovative analytical approaches to improve how clinical studies are designed, executed, monitored, and interpreted. They are comfortable working across multidisciplinary teams, capable of bridging scientific and technical domains, and motivated to leverage AI, machine learning, real-world evidence, and digital health technologies to accelerate drug development and improve patient outcomes. Location The position is based in our Paolo Chiesi R&D Campus, Parma, Italy, with a flexible hybrid working model. Budgeted salary range The budgeted salary range approved for this role is between €46.000 and €57.500 . This range reflects the typical compensation expected for candidates with the experience and expertise required for the position. Final offer may vary based on the selected candidate's skills, experience, qualifications, overall profile, and internal equity considerations. This role is eligible to participate in an annual bonus scheme, subject to company and individual performance. In addition, we offer a comprehensive benefits package including p ension, private medical insurance, wellbeing programme, flexible benefits programme and more. What we offer No matter where your path starts at Chiesi, it leads to inspiring possibilities. Your future is our focus, and we are committed to nurturing your development in our dynamic, friendly environment with access to resources and training every step of the way. We provide top-class benefits, including comprehensive healthcare programs, work-life balance initiatives, and robust relocation support. Our salary package is competitive, comprising a basic salary, performance bonuses, and benefits benchmarked against the external market. Additionally, we offer flexible working arrangements, remote work options, and tax assistance services for foreign colleagues, all designed to help you thrive. Chiesi is an equal opportunity employer committed to hiring a diverse workforce at all levels of our business. All qualified applicants receive consideration for employment based on attitude and merit, without regard to race, national origin, age, sex, religion, disability, sexual orientation, marital status, military status, gender identity or expression, or any other basis protected by applicable laws. This policy applies to all aspects of employment, including hiring, transfer, promotion, compensation, eligibility for benefits, and termination.