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DuPontPosted 2 months ago

IT Business Analyst – Innovation Excellence (m/f/d)

$31,200–$31,200 year

On-siteAvilés, Asturias, Spain

Full TimeEnterprise

Job Summary

IT Business Analyst at DuPont's Innovation Excellence team driving digital transformation across global R&D. Partner with scientists, lab managers, and business stakeholders to uncover challenges, map current processes, define future-state capabilities, and prioritize high-value digital solutions. Translate complex laboratory workflows into clear requirements, user stories, and MVP concepts; ensure solutions are grounded in business outcomes and user experience. Collaborate with architects, developers, vendors, and program teams to design scalable, fit-for-purpose solutions and evaluate options from business and technical perspectives. Prioritize features using business value, feasibility, user adoption, and speed-to-value; support rapid prototyping and iterative development. Define acceptance criteria and guide UAT, gather pilot feedback, and drive continuous improvement. Leverage tools such as Copilot, Power Platform, and AI-enabled prototyping to validate ideas quickly; support change management, training, and adoption activities. Build digital excellence across R&D by understanding laboratory processes, scientific data flows, and integration with systems like ELN, LIMS, SAP, and IP21; act as a trusted partner bridging scientific needs with digital possibilities.

Required Qualifications

  • Bachelor's or Master's degree in Science, Engineering, Information Systems, or a related discipline.
  • Experience in business analysis, product-focused solution design, requirements management, process improvement, or digital transformation initiatives.
  • Fluent in English.
  • Strong ability to engage stakeholders at all levels and translate business challenges into actionable solutions.
  • Analytical mindset with excellent facilitation, problem-solving, and communication skills.
  • Experience supporting digital platforms, systems implementations, or process optimization programs in complex environments.
  • Curiosity for understanding scientific or laboratory operations and identifying opportunities for technology-driven improvement.
  • Familiarity with agile delivery approaches and iterative solution development.

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