Customer Success Intern (Mirakl Ads)

Location: Paris, France; Paris office

Internship compensation: €1,200–€1,400 per month, depending on profile.

Company

hirify.global provides an enterprise marketplace and retail technology platform, including marketplace, multichannel selling, retail media, and commerce infrastructure solutions.

What you will do

• Support client workshops, onboarding sessions, training materials, and business reviews.
• Monitor advertising network KPIs and prepare regular performance reports.
• Analyze Retail Media data to identify trends and growth opportunities and turn findings into client recommendations.
• Research Retail Media, eCommerce, digital advertising, and competitive dynamics.
• Document best practices, processes, and client insights while exploring AI tools to improve reporting and client experience.

Requirements

• Currently pursuing a Bachelor's or Master's degree in Business, Engineering, Marketing, Data, or a related field.
• Demonstrated interest in eCommerce, marketplaces, Retail Media, or digital advertising.
• Strong analytical, problem-solving, organizational, and attention-to-detail skills.
• Ability to work across multiple stakeholders in a fast-paced, international environment.
• Fluent English and French, written and spoken, required.
• Comfort working with AI tools to improve productivity and output quality.

Nice to have

• Previous experience with data analysis or client-facing projects, academic or professional.

Culture & Benefits

• Six-month internship starting in January 2027.
• Tailor-made integration path and evolving assignments focused on skills development.
• Opportunity to work with international teams at a growing French technology company.
• Workplace well-being activities including breakfasts, sports and yoga classes, and aperitifs.

Hiring process

• Recruiter CV screening followed by a 10-minute AI-powered screening conversation, to be completed within three days.
• Introductory recruiter call.
• Business interview with the future manager and a team member using structured STAR-method questions.