About the job

Our client is looking to hire an ESG Quant Analyst to join their growing Sustainable Investment team. This is a unique opportunity for someone with a passion for sustainability and data science to help drive innovation in responsible investing. You'll play a key role in developing the firm's ESG research, analytical tools and proprietary datasets.

Key Responsibilities:

• Lead and support engagement with publicly listed companies across global markets, discussing ESG-related topics and monitoring progress against engagement objectives
• Research ESG risks, opportunities and controversies affecting portfolio companies, translating findings into clear and actionable investment insights
• Capture intelligence from company meetings and integrate qualitative observations into structured research and proprietary datasets
• Use Python, SQL and modern AI tools to source, clean, structure and analyse large structured and unstructured datasets
• Develop and maintain high-quality stewardship records, case studies, internal research notes and external reporting
• Partner closely with investment teams to identify themes that can strengthen investment research and ESG analysis
• Contribute to the development of scalable research processes, analytical models and AI-enabled tools that enhance stewardship and ESG decision-making
• Help identify new sources of ESG data and innovative analytical techniques that improve research quality and investment outcomes

Candidate Profile:

• 1-3 years of relevant work experience on the buy-side or sell-side with a genuine interest in sustainable investing
• Undergraduate degree in a quantitative discipline such as finance, economics, mathematics, statistics, computer science or a related field
• Strong programming skills, particularly in Python and SQL, with experience manipulating and analysing large datasets
• Experience using modern generative AI tools and large language models to improve research workflows and data analysis
• Excellent analytical and critical thinking skills with the ability to identify patterns, draw conclusions and communicate insights clearly
• Strong written and verbal communication skills, including confidence engaging with companies and presenting findings to both technical and non-technical audiences
• Excellent organisational skills with the ability to manage multiple priorities and work collaboratively across international teams
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