Student Assistant, ESG - Climate & Data

ASCENDIS PHARMA A/S; Gentofte Kommune; On-site; DKK 134,000 - 201,000; Part time

Job summary

Ascendis Pharma is seeking an ESG Student Assistant to support the development of ESG data processes with a focus on greenhouse gas emissions. You will work with data from across our organization and supply chain to help calculate and validate Scope 1, 2 and 3 emissions.

You will join a small ESG team, contribute to data documentation, KPI preparation and broader ESG reporting for an international company headquartered in Denmark.

Qualifications

• Currently starting the first year of a Master’s program with a quantitative focus.
• Strong passion for sustainability and data-driven analysis.
• Interest in greenhouse gas accounting and ESG reporting.

Responsibilities

• Support collection, analysis and validation of environmental data across the organization and supply chain.
• Assist GHG calculations and maintain data, factors and calculation files.
• Document GHG methodologies and data collection processes for reporting and assurance.
• Prepare sustainability KPIs and contribute to ESG reporting.
• Collaborate with ESG team on data quality improvements.

Skills

Analytical skills

Data analysis

Excel

Education

Master's student in environmental engineering or related field

Tools

MS Office

Job description

Are you passionate about corporate sustainability, comfortable working with data, and looking to learn more about ESG reporting in an international company?

If so, now is your chance to join Ascendis Pharma as our new ESG Student Assistant.

Ascendis Pharma is a global biopharmaceutical company committed to making a meaningful difference in patients’ lives. Guided by our core values of Patients, Science, and Passion, we are applying our innovative TransCon® technology platform to fulfill our mission of developing new therapies that demonstrate best-in-class potential to address unmet medical needs.

At our headquarters in Hellerup, Denmark, research facilities in Heidelberg, Germany, and additional offices across Europe and the United States, we are advancing programs in our Endocrinology Rare Disease and Oncology portfolios. We also collaborate with partners on the development of TransCon-based products in other therapeutic areas and markets.

We are seeking a student assistant to join our ESG team, where you will support the development of our ESG data processes, with a particular focus on greenhouse gas emissions. In this role, you will work with data from across our organization and supply chain, support the calculation and validation of our Scope 1, 2 and 3 greenhouse gas emissions, and help us continuously improve the quality and traceability of our environmental data.

You will join a team of 9 dedicated colleagues, working within Compliance, Risk Management, Data Privacy and ESG.

Your main tasks will include:

• Supporting the collection, analysis and validation of environmental data across the organization and our supply chain, with a particular focus on Scope 1, 2 and 3 greenhouse gas emissions
• Supporting GHG calculations and maintaining underlying data, emission factors, assumptions and calculation files
• Maintaining documentation of GHG calculation methodologies and data collection processes for external reporting and assurance
• Supporting environmental data analysis and preparation of sustainability KPIs
• Contributing to broader ESG reporting as relevant

Your qualifications

Ideally, you are starting the first year of your Master's studies in environmental engineering, sustainability, environmental science or another relevant field with a strong quantitative component.

Most importantly, you are passionate about sustainability, enjoy working with data and solving analytical problems, and want to learn more about greenhouse gas accounting and ESG reporting within an international company.

you have:

• Strong analytical skills and confidence working with quantitative data
• Excellent working knowledge of MS Office, particularly Excel, and the ability to work with complex datasets
• High attention to detail and a structured approach to tasks and documentation