Careers

Role
Join an innovative climate research institute dedicated to advancing the understanding and application of climate risk assessments, developing innovative methodologies. This is a position for a researcher who wants to do both: publish rigorous, peer-reviewed work and see it shape the way financial institutions actually price and manage climate risk.

At the EDHEC Climate Institute (ECI), you will be the lead architect of our climate risk methodology for real estate, a growing priority for lenders, insurers, and long-term investors navigating a rapidly changing regulatory and physical landscape. You will define how ECI approaches the real estate sector, build the analytical frameworks that underpin our tools and client deliverables, and publish the work that establishes ECI's intellectual leadership in this space.

The ideal profile has a strong research foundation at PhD level combined with meaningful exposure to how real-world financial institutions, consultancies, or real estate operators actually use (and misuse) quantitative risk frameworks. If you have been looking for a position that bridges rigorous academic output with genuine market impact, this is it.

Responsibilities

• Build ECI's real estate climate risk methodology Design and lead the development of integrated frameworks to assess climate-related financial risk in real estate, covering both transition and physical dimensions. This means understanding the risk transmission channels from hazard or policy shock, through asset-level physical and financial vulnerability, to portfolio-level financial outcomes and translating that chain into models that are both analytically sound and operationally usable by financial institutions. The physical and transition risks shocks will be provided by other team member, so what is required is a deep understanding of how to integrate them.
• Anchor methodology in real estate financial fundamentals Your framework must speak the language of real estate finance. That means grounding assessments in how climate variables, energy costs, retrofit CapEx, stranded-asset risk, insurance availability, regulatory compliance costs, flow through to valuation, LTV, PD/LGD, and broader portfolio risk metrics. Financial model literacy applied to real estate is central to this role.
• Develop and adapt quantitative tools Adapt and extend models relevant to the built environment (e.g., CRREM, building archetype/stock models, LCA frameworks) with a focus on understanding the conceptual architecture behind them, the assumptions, boundary conditions, and transmission mechanisms, rather than applying them as black boxes. Integrate EPC/energy label datasets; assess coverage and quality; propose calibration and substitution strategies. Build reproducible, well-documented pipelines.
• Publish and establish intellectual presence Publish in peer-reviewed scientific and finance journals. You will also contribute to conferences, policy forums, and industry workshops to develop ECI's profile in this space.
• Be the real estate expert within ECI's broader research ecosystem Work in close collaboration with ECI's other research teams; including climate scenarios, geo-sectoral physical risk, and regulatory intelligence; to integrate real estate perspectives into cross-cutting tools and products. You will be the go-to expert for real estate within the institute, contributing to ECI's flagship tools and shaping how real estate risk is represented across our research agenda.
• Engage with the financial industry Work directly with financial institutions, real estate operators, and regulators to align ECI's methodologies with evolving regulatory requirements (SFDR, CSRD, EBA guidelines) and practical decision-making workflows.

What We Are Looking For

• Background and training A PhD (or Master's with equivalent research depth) in a quantitative field with strong relevance to the real estate sector and the quantification of its underlying financial risks. We are specifically interested in profiles that combine academic rigour with real-world exposure; whether through PhD research conducted in partnership with industry, post-doctoral work in an applied setting, consultancy experience alongside publication activity, or a transition from practice back into research.
• Real estate financial modelling Solid understanding of how real estate assets are valued and financed: DCF and income capitalisation approaches, LTV and debt service coverage ratios, PD/LGD frameworks, and how physical or regulatory shocks transmit into these financial metrics. 
• Understanding of climate risk transmission in the built environment Conceptual fluency with how both transition and physical climate risks propagate through real estate assets. On the transition side: how carbon pricing, energy performance regulations, and evolving market preferences interact with operating costs, asset values, and financing conditions. On the physical side: how hazard frequency/severity translates into damage, insurance cost, and asset obsolescence. Deep prior specialisation in one dimension is fine; the capacity to reason rigorously about the other is required.
• Quantitative and technical skills (recommended) Python (or equivalent) for model development and data analysis. Experience working with building-level or portfolio-level datasets (EPC registries, energy audit data, transaction/valuation data). Familiarity with retrofit economics, abatement cost curves, sequencing of measures, technical/economic feasibility assessment; is a plus. Prior work with CRREM, building archetype models, though what matters most is the ability to understand and critically evaluate the assumptions behind such tools.
• Communication and collaboration Ability to write clearly for both academic and practitioner audiences; from methods papers to client-facing notes. Comfort working across disciplines (climate science, engineering, economics, data engineering, finance). Track record of, or clear appetite for, collaborative research involving external partners or industry stakeholders.

Attractive salary and bonus, healthcare and pension plan coverage.

The salary will be determined according to EDHEC's pay scale, the candidate's qualifications and experience.

To apply, please send your CV and a cover letter to: [email protected].

EDHEC Climate Institute is looking for a motivated and technically strong Data Science Intern to support the development of our infrastructure ratings. The successful candidate will collaborate closely with senior team members on real-world data science problems.

The production of climate risk ratings relies on:

• Sophisticated climate risk models complemented by robust analytics
• A structured, production-grade codebase supporting model simulations and the generation of ratings

The code structure must be designed with reliability, efficiency, and maintainability as core principles. The successful candidate will help improve existing code and structures, and assist in developing new ones. This requires strong coding and organizational skills.

This internship is a great opportunity to work at the interface of climate science, finance, and regulation, while developing strong analytical and coding skills.

Moreover, this internship is a potential pathway to a full-time Junior Data Scientist position, subject to performance.

Duration: 6 months

Key Responsibilities

• Assist in improving the maintainability, efficiency, and robustness of the codebase
• Assist in building and maintaining data pipelines
• Develop analytical tools to improve the traceability of results
• Support data analysis, modeling, and data processing tasks
• Produce clean, well-structured, and well-documented code
• Contribute to the documentation of methods and workflows

Required Skills & Qualifications

• Strong general programming skills, with a focus on logic, readability, efficiency, automation, and maintainability
• Solid proficiency in Python, ideally with experience in object-oriented Python
• Familiarity with common Python libraries for data science (e.g. pandas, numpy)
• Experience with collaborative version-control tools (Git)
• Meticulous and analytical mindset, with a strong interest in problem-solving
• Ability to work independently under minimal supervision
• At least a bachelor’s degree in a technical curriculum such as computer science, finance, economics, or physics

Nice to Have

• Proven experience with data science projects
• A master’s degree in a technical curriculum
• Basic knowledge of financial concepts and modelling
• Interest in climate change–related topics

Profile We Are Looking For

You are rigorous and enjoy solving concrete problems with data. You care deeply about code quality and take pride in improving your code’s readability and efficiency.

You are curious and keen to expand your knowledge in climate finance.

You want to grow as a professional data scientist, and see this internship as a solid stepping-stone towards that objective.

We value clean, production-ready code as much as correct results.

To apply for this offer, please send a CV and a cover letter to: [email protected].

Join a growing and global team focused on measuring climate risks and bringing new data and rating services to investors. As climate physical and transition risks increasingly impact investors’ portfolios and corporate balance sheets, the need for high-quality climate risk data and assessment tools is rising.

EDHEC Climate Institute is looking for a Sustainability Data Analyst Intern to support our team in collecting, processing, and analysing sustainability-related data for infrastructure assets. This internship offers a unique opportunity to gain hands-on experience in data extraction, carbon emissions analysis, and geospatial analysis.

Beyond core data processing tasks, the internship can be tailored to the candidate’s interests and expertise. This could include research projects and case studies on climate risk assessment and financial materiality analysis, allowing you to contribute meaningfully while expanding your expertise.

Duration: 3 to 6 months

Key Responsibilities

• Data Collection & Cleaning: Verify, clean, and structure sustainability- and climate-related data from reports and other sources.
• Data Quality & Accuracy Checks: Conduct detailed data validation and consistency checks to ensure high data quality across datasets.
• Accuracy Verification: Ensure the precision of extracted data, including asset attributes and boundaries.
• Geospatial Analysis: Use tools such as QGIS or ArcGIS to extract, review, and analyse asset boundaries and spatial data.
• Knowledge Management & Documentation: Support the setup and maintenance of team documentation, including Notion workspaces, internal wikis, and process guides to improve data workflows and knowledge sharing.

Ideal Candidate

We are looking for candidates who:

• Have a strong interest in sustainability, climate risks, and environmental data.
• Have some experience and/or a strong interest in climate-related research or data work.
• Are highly detail-oriented, with a strong eye for identifying data inconsistencies and errors.
• Are organised and methodical, with an interest in improving processes and documentation.
• At least a bachelor’s degree in a technical curriculum such as computer science, finance, economics, or physics
• Can work independently, take ownership of tasks, and are eager to learn new skills.
• Preferably have basic proficiency in Python for data processing or analysis.
• Preferably have prior exposure to geospatial data and tools such as QGIS or ArcGIS.
• Preferably have experience setting up or maintaining documentation tools (e.g. Notion, Confluence, or internal wikis).

What You’ll Gain

• Practical experience in sustainability data analysis and climate risk research.
• Hands-on exposure to geospatial analysis and real-world asset data.
• Experience working with data quality assurance and internal knowledge systems.
• A flexible internship experience tailored to your skills, interests, and performance.
• The opportunity to contribute meaningfully to a mission-driven and growing team.

To apply for this offer, please send a CV and a cover letter to: [email protected].