DATA STEWARDSHIP MANAGER

Nous construisons l’avenir de la dermatologie médicale en nous concentrant sur les besoins non satisfaits des patients et en donnant aux personnes l’espace pour penser à leur manière, prendre des responsabilités et créer un impact qui a du sens. Notre raison d’être est simple : transformer la vie des patients en répondant à de vrais besoins. Nous travaillons avec rigueur, agissons avec courage, gardons les choses simples et orientons notre innovation là où elle fait vraiment la différence.

Reconnus comme Top Employer en Espagne depuis 2008 et en Allemagne depuis 2025, nous continuons d’investir dans un environnement où chacun peut grandir et aller de l’avant. Si tu penses différemment, tu as ta place ici. MISSION As a Data Stewardship Manager you will join the Analytical & Formulation Sciences team within the Molecules organisation in Almirall R&D. You will drive and advance the organisation's digital and data strategy, by representing Molecules in shaping the Almirall R&D digital and data roadmap, partnering closely with scientists, laboratory teams, Data Science, and IT/Digital to translate scientific needs into aligned, scalable digital solutions.

The role will build the trusted scientific data foundation needed to accelerate R&D, strengthen decision-making, and unlock future digital and AI-enabled capabilities.

Represent the Molecules organisation in shaping and implementing the broader R&D digital and data roadmap, ensuring its scientific needs, priorities, and workflows are incorporated into scalable digital solutions.

• Lead scientific workflow and data discovery sessions with laboratory teams, mapping experimental processes, data flows, calculations, decision points and exceptions to identify opportunities for standardization, automation and reuse.
• Drive adoption of agreed data standards and digital workflows by developing guidance, training users, supporting onboarding and acting as a trusted partner to laboratory teams during changes in tools and ways of working.
• Partner with IT/Digital, Data Sciences, and laboratory teams to translate the R&D digitalization roadmap into harmonised data structures and practices across analytical techniques, therapeutic modalities, and laboratories.
• Establish and coordinate the stewardship and governance of analytical and drug development data generated by internal laboratories and external partners, providing the trusted data foundation required to deliver the R&D digitalization roadmap.
• Define and maintain data standards, metadata, data dictionaries, taxonomies, controlled vocabularies, critical data elements, and FAIR principles.
• Translate scientific needs into data and system requirements for ELN, LIMS, repositories, and other digital solutions.
• Ensure data practices remain lean and efficient in non-GxP environments while meeting applicable data integrity, quality, regulatory, and GxP requirements where needed.
• Enable automation, advanced analytics, and AI through fit-for-purpose scientific data.
• Coordinate effectively with IT/Digital, Data Science, Quality, Regulatory, and other R&D stakeholders.

Bachelor’s or Master’s degree in Pharmaceutical Sciences, Biochemistry, Data Science, or a related discipline is desirable.

• Experience in pharmaceutical or BiotechMI R&D, analytical development, laboratory informatics, or scientific data management ecosystems is a must.
• Working knowledge in programming languages (e.g. Python, SQL etc.) is desirable.
• Ability to manipulate, analyse, and automate scientific data workflows is a must.
• Strong understanding of analytical laboratory workflows and associated scientific data.
• Practical knowledge of data governance, including metadata, data quality, data lineage, data ownership, taxonomies, and data lifecycle management.
• Experience translating scientific requirements into structured data and technology requirements.
• Strong communication, problem-solving, facilitation, and stakeholder-management skills, with the ability to explain complex scientific and data concepts to laboratory, technical and senior leadership audiences.

Experience with laboratory systems such as ELN, LIMS, CDS, SDMS, or scientific data repositories.

• Familiarity with analytical techniques and their associated data.
• Experience with data harmonisation, migration, integration, or laboratory-system implementation.
• Understanding of FAIR data principles, pharmaceutical data integrity, and GxP expectations.
• Exposure to automation, advanced analytics, AI, and machine learning in scientific environments.
• Scientific mindset combined with a pragmatic, collaborative, innovative, and change-oriented approach.
• Fluency in spoken and written English is essential, other languages are a plus.

L’offre est publiée sur le site de Almirall. Ouvrez l’offre originale ↗ pour y déposer votre candidature. Screeningpass ne remplit pas de formulaire à votre place.

Lancez une recherche de contact depuis cette page. Screeningpass vous propose jusqu’à trois personnes liées au poste. Vous choisissez celle à qui écrire, puis Screeningpass cherche son e-mail professionnel et prépare un message. Vous le relisez et l’envoyez vous-même avec Gmail. Une adresse e-mail n’est pas toujours disponible, et une réponse n’est jamais garantie.

Une recherche coûte 1 crédit. Le crédit vous est rendu si la recherche échoue. L’inscription offre 3 crédits, soit 3 recherches.

Screeningpass rassemble des offres de stage, d’alternance et d’emploi publiées par les entreprises. Pour une offre, Screeningpass trouve une personne à contacter dans l’entreprise, cherche son e-mail professionnel et prépare un message à partir de votre CV. Voir le fonctionnement en détail.