Sustainability Quantitative Analyst (GVA/LDN) - Full time

A career at the Lombard Odier Group is something to be proud of. Our mission is to protect and grow our clients’ wealth - but not by any means necessary. Sustainability is at the heart of everything we do and we treat our clients’ wealth as if it were our own. We protect our clients’ assets for the long-term using expertise and innovation, all underpinned by our Rethink Everything philosophy. Our colleagues are the foundation of our success. We employ people at different life stages, from graduates to executive level leaders. The one thing they all have in common is that they seek to challenge the status quo, are imaginative and have the ability to offer a fresh perspective.Lombard Odier Investment Managers (“LOIM”) is the asset management arm of the Lombard Odier Group. With more than 120 investment professionals, we are a global business with a network of 13 offices across Europe, Asia and North America. LOIM has a unique approach to investment, combining the best of alternative and traditional asset management, to offer its clients a diversified range of investment solutions, including a number of new and innovative approaches.To further strengthen our Sustainability Investment Research & Strategy team, we are looking for a Geneva basedSustainability Quantitative AnalystThe candidate will report to our Deputy Head of Sustainability Research.Summary: Support the team in the development of additional tools to assess the transition of companies and portfolios to a Circular, Lean, Inclusive and Clean (CLIC™) economy. These tools include our existing Lombard Odier Portfolio Temperature Alignment (LOPTA) tool, as well as new metrics under development related to circularity, biodiversity and planetary boundaries. Assist in ensuring robust and highly quality production release of all the metrics developed by the team by monitoring daily data uploads. Help building any relevant tool in order to enhance the use of the metrics by all investment teams.Primary Responsibilities:Support the implementation of proprietary metrics, including a specific focus on the integration of these models into our existing Python/SQL environment; ability to work on complex assignments with an high attention to detail and excellent coding practice is essential.Development of proof-of-concept methodologies aimed at the ability to provide quantitative scores representing alignment to identified sustainability challenges across a large universe of companies.Conversion of proof-of-concepts into a full-scale production environment (based on Python/SQL/quant platform interfaces).Focus on the next releases of the team’s flagship LOPTA tool as well as new metrics under development by the team focusing on the assessment of company’s environmental impact, resource footprint, and alignment to sustainable development goals (SDGs).Build in datasets derived from unstructured data, text-based sources and otherwise, drawing on machine learning, natural language processing, and similar techniques.For this position, we are looking for:Master's in Mathematics, Computer Science or any other quantitative fieldExperience in creating or working with data architecture / data science projectsCoding fluency and experience with Python ; Java, C++ are a plusStrong problem solving skillsFluent in English, French would be a plusTeam player, meticulous, open-minded, curiousStrong interest in sustainabilityKnowledge of machine learning techniques (interest in natural language processing would be a plus) and their real-world advantages and drawbacksLOIM is an equal opportunity employerWe are committed to creating a diverse and inclusive work environment, where talented people inspire the organization with a diversity of thought, background, experience and identity to reinforce our innovation and deliver excellence. We firmly believe this is how we will continue to thrive. To deliver on this, we have actively embedded Diversity & Inclusion in our business strategy.If you recognise yourself in this description, then please do apply. We look forward to hearing from you.