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EcoVadis is seeking an AI Governance Expert to join its AI Center of Excellence. You will drive governance across AI and machine learning initiatives, ensuring regulatory alignment and responsible AI practices throughout products and processes.
You will coordinate with AI engineers, legal, sales, procurement, and enterprise architecture teams to mitigate risks, communicate policies, and support transparent reporting. This hybrid role is based in Barcelona with a flexible in-office schedule.
EcoVadis is a leading provider of business sustainability ratings. We analyze data and build sustainability scorecards that give companies actionable insights into their environmental, social, and ethical risks.
We are looking for a highly motivated AI Governance Expert to join our growing AI Center of Excellence, responsible for using AI and machine learning to drive innovation across the organization.
You are collaborative, highly motivated, and eager to grow your career in an international, evolving, and forward-thinking environment. You possess excellent verbal and written communication, critical thinking, and analytical skills.
EcoVadis commits to equity, inclusion, and reducing bias in its hiring processes. EcoVadis does not accept any form of discrimination based on characteristics such as color, national or ethnic origin, ancestry, citizenship, religion, beliefs, age, sex, gender identity, sexual orientation, neurodiversity, disability, parental status, or any other protected characteristic. To reduce bias, applicants are encouraged to remove personal details such as photos, marital or parental status, religion, gender, postal code, university name or graduation date, past leave details, and nationality. Applicants should confirm eligibility to work in the job location.
EcoVadis’s recruitment processes do not include AI systems that make autonomous decisions impacting individuals’ rights without human oversight. All inputs and outputs of the system have been validated by humans and answers are based on algorithms that analyze previous data with which the system has been trained.