Our client is a global asset management firm and an industry leader in sustainable investing. This role will work as part of the Sustainable Research team and be responsible for the quantitative data produced by the team and provide quantitative support on various aspects of the research process. This is an exciting opportunity for an individual with knowledge of traditional datasets and an interest in exploring the developing field of ESG data. Key responsibilities: Work closely with Head of ESG and the investment teams across equities and fixed income strategies to support the integration of ESG data into the investment process. Maintain and develop the internal data management platform and ensure that data used by the research team is correctly managed and fit for purpose. Develop, maintain and upgrade data models (e.g., estimation models for carbon emissions and water consumption). Contribute to the design and implementation of methodologies for portfolio assessments including climate risk metrics. Work on various data projects as required (for example, automating data, enhancing systems functionality, review of external methodologies). Manage relationships with ESG data providers. Ideal Candidate Profile: 3-5 years’ work experience in a quantitative, data scientist or similar role in asset management, banking or fintech sector. Experience working with ESG data is helpful but not essential. Strong coding skills are essential, preferably in Python or R. Interest in sustainable investing/ESG related issues. Ideally knowledge of Bloomberg and other data platforms. Degree educated in a relevant field, preferably with a quantitative focus. Collaborative approach to work. Excellent analytical and problem-solving skills. Mason Blake acts as an employment agency for permanent recruitment and employment business for the supply of temporary workers. Mason Blake is an equal opportunities employer and welcomes applications regardless of sex, marital status, ethnic origin, sexual orientation, religious belief, or age. Apply for this job #J-18808-Ljbffr
