Global HR/Talent Intern
QuantisAbout the role
Quantis’ Talent team strives to support the continuous growth and evolution of the company. We are looking for an HR Intern to assist our Global Talent team. Based in our Paris office, your mission will be to support the team on HR Reporting, Performance Management and Talent Acquisition topics. Occasionally, you may be asked to provide support to our Learning & Development team.
As our HR/Talent Intern, with the support of the Group Performance Management Lead and the Group Talent Acquisition Lead, you will be responsible for:
End-of-Year Performance Review Cycle
- Assist in running the end-of-year performance review cycle at a global level
- Produce communication materials for employees, managers, and HR teams in local markets
- Monitor the completion of each step of the process and produce associated reports
- Build and maintain Excel models to support decision-making processes
Compensation Review Exercise
- Maintain and improve internal tools to support decision-making (Excel models)
- Assist with follow-ups on compensation review activities
Recruiting: Support the recruitment team on their daily tasks and pipelining
- CV review & sourcing
- Coordination of interviews & communication with candidates
- Management of the Talent Pool
- Maintenance of the applicant tracking system
- Contribution to improvement of hiring process
- Help with communication of recruitment guidelines across the company
- Support recruitment related trainings
People Capacity Monitoring and Planning
- Help monitor and plan our people capacity using HR data and inputs from local markets
- Run analysis and help prepare synthesis of key learnings to assist operational management
YOU WILL BE SUCCESSFUL IF:
- You’re motivated to develop your HR knowledge and skills on critical HR topics, from planning and recruiting to performance and compensation, in an environment working towards building a sustainable future and aligning businesses with Planetary Boundaries.
- You possess a strong sense of rigour and excellent quantitative analytical skills.
- You have previous internship / work experience using Excel and PowerPoint, master these tools and want to further improve your skills.
- You are familiar with and eager to develop your skills in data visualization.
- You have strong organization and time management skills.
- You love human contact and have strong communication skills.
- You are service oriented and have team spirit and can-do attitude.
- You are curious and willing to learn more about both HR and sustainability.
- You communicate effectively in fluent English (both oral and written communication). French would be a big plus.
- You like to be part of an intercultural team.
WHY YOU’LL LOVE QUANTIS
Quantis is a leading sustainability consultancy pioneering approaches to solve critical environmental challenges. For nearly two decades, our dynamic and visionary team has partnered with organizations across the globe to transform their industries and pave the way for a planetary economy that aligns business with nature. We strive to be agents of change, helping companies transform from business as usual to business at its best.
We believe that sustainable transformation is possible and within our power. We’re contributing to this transformation by combining the latest science with strategic business insights. Our advice enables global leaders in the consumer goods and finance industries to understand how to reduce their environmental impacts, implement change successfully, and operate within planetary boundaries.
Motivated by this common purpose, our 300+ talented professionals cultivate a unique, collaborative culture that we call the Quantis Spirit. We are innovative. We are impact oriented. We are science-based. We are Quantis.
Join us!
SOME OTHER DETAILS TO CONSIDER:
- Location: Paris, 75002 - hybrid work scheme (mix of office presence and work from home)
- Minimum requirements: You must be enrolled at a university / business school (HR studies or relevant) and have a valid “convention de stage”. Pr
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