ESG Data Scientist

• How exposed is my portfolio to severe flooding and other physical climate risks?
• Which companies are most impacted by talent scarcity and employee engagement?
• What do patent filings tell us about the effectiveness of company R&D investments?
• Can text parsed from news articles provide information on a company’s positive sustainable impact?

• Identify and evaluate new data sources (structured and unstructured) that provide unique and proprietary ESG insights on investments and portfolios
• Develop new ESG models that distill data into actionable insight across asset classes (equity, municipal bonds, private assets, real estate, infrastructure)
• Apply machine learning, deep learning, natural language processing, parsing tools and other data science techniques to improve the effectiveness of ESG models
• Conduct back-testing and scenario analysis of proposed methodology enhancements to understand implications on ESG Ratings
• Use statistical methods and programing to analyze, interpret, and visualize data
• Develop intelligent automation initiatives that enables analytical predictions, drives innovation and improves productivity
• Work with stakeholders to identify the business requirements, understand distinct problems and expected outcomes, and model and frame innovative solutions
• Collaborate with other teams such as Data, Analytical Quality Assurance and Application Development to test and advance methodologies

• Advanced skills in data science and programing language (e.g. Python) is a must-have; experience in Microsoft Excel or geospatial analysis (e.g. ArcGIS, QGIS) is preferred
• Knowledge of machine learnings models such as NLP is preferred
• Strong analytical and quantitative skills with prior experience in the data manipulation and development of quantitative models
• Ability to overcome data quality challenges with creative solutions, including familiarity of various types of source data (unstructured, semi-structured) with multiple level of granularities (e.g. product, customers, geo-spatial, demographic)
• Excellent verbal communication skills to facilitate strong relations with a global team of industry research analysts
• High motivation for joining a dedicated, technically savvy, and enthusiastic team

Desired Experience:

• 2-5 years of full-time professional experience in quantitative research or data science role, prior exposure to capital markets is preferred
• Bachelors' degree required; Advanced degree in related field (Quantitative finance, computer science or engineering, econometrics, mathematics) is preferred
• Experience with ESG analysis is not a pre-requisite, but candidate should have a demonstrated interest in how ESG issues are integrated into investment decisions