ESG Research Associate - Scoring Specialist - Boston
Arabesque, United States
Job Description
About Arabesque S-Ray
Arabesque is a global investment management and technology firm that brings a new dimension to investing, using machine learning techniques, quantitative models, and big data to assess the performance and sustainability of globally listed companies and to construct investment portfolios. Arabesque offers investment solutions to clients and provides third parties with its sustainability analysis, originating from our proprietary technology, Arabesque S-Ray . Arabesque S-Ray is a technology firm that combines sustainability data, big data and machine learning to provide data products and research to empower investors, corporates and other stakeholders to make more sustainable decisions.
Our story is one of a partnership between leaders in finance, science, and sustainability to accelerate the transition to a more sustainable future. It is our mission to make sustainable and responsible investing economically attractive and available to all, and to empower people through data. We firmly believe that finance can be a catalyst of change.
With headquarters in London and offices in Frankfurt, Singapore, and Boston, the firm is in a period of rapid international growth in 2020.
The ESG Research Team
We are responsible for designing, building, and managing Arabesque S-Ray’s data products and research models. We are looking for a technically gifted, sustainability expert who likes to work in a collaborative environment to innovate, advance, and contribute to the development of our ever-evolving S-Ray technology. You will be part of the global ESG research team with 50+ experts across ESG data, climate data, climate models, statistics, econometrics, data science, and applied investment quant. You will be involved in the development of new scoring systems, sourcing original raw-level metrics, aligning scoring models with global regulations, advising on integration techniques into investment solutions, and ensuring new products and research are well-understood by our global clients. Additionally, we are looking to integrate this research associate into our bespoke scoring products in collaboration with design partners across global asset managers, asset owners, media corporations, and consultants.
Arabesque strongly believes that a research team made up of diverse ethnic, religious, social, educational, gender and sexual orientation backgrounds best contributes to the mission and growth strategy of the business going forward. We, therefore, strongly encourage applicants from every background to apply and join our exceptional team.
Requirements
Your Role amp; Responsibilities
We are looking to hire a new ESG Research Associate with experience using ESG data and integrating that information into scoring models (from simple to complication methodologies) to join our global research team and contribute to Arabesque’s growth. You will be responsible and accountable for contributing to Arabesque S-Ray’s data, research models, and ratings products.
You Are Expected To
- know about the intricacies of ESG, climate, and non-financial data;
- know how to handle ESG, climate, and non-financial data;
- apply knowledge and expertise using Python to the design of new scoring models;
- utilize database query language and Python to manipulate large datasets - both structured and unstructured inputs;
- liaise with the Global Research Office and Global Head of Sustainable Investing amp; ESG Research on designing and calibrating bespoke scores.
The above list of job duties is not exclusive or exhaustive and the post holder will be required to undertake such tasks as may reasonably be expected within the scope and grading of the post.
We Are Keen To Hire Professionals Who
- are highly experienced with ESG data either within ESG ratings providers, asset management research, asset owner research, investment consultant research, think tanks focused on sustainability, or academic research institutes;
- have vast experience working with Python, with a desire to apply existing code and build new programming skills to solve new empirical challenges;
- feel comfortable on-boarding, analyzing, and quality-assuring large amounts of data, including handling data from multiple sources with varying levels of data quality;
- possess a fluent command of the English languagespeaking and writingand have a desire to share knowledge and expertise across research team and design partners;
- are motivated and passionate about solving empirical problems and building innovative data tools, scoring models, and products;
- are not afraid of new empirical challenges and mastering a new area of expertise;
- enjoy hands-on work with programmin