ESG Research Senior Analyst

The Senior Analyst, Indicators and Metrics Team, is responsible for the design, development, implementation, and maintenance of all ESG indicators and ESG metrics within Morningstar Sustainalytics. The Indicators and Metrics team leverages technical applications and content expertise to ensure a cohesive approach to our portfolio of product-agnostic indicators and metrics. A key responsibility of the team is to support ongoing projects to automate data collection for indicators and metrics. 
 
Collaboration is key, and close interaction with the ESG data team, research teams, IT teams, and product excellence team is required for the successful development and maintenance of indicators and metrics.  

 
Job responsibilities:  

- Lead and support the development of new indicators and metrics as well as improvements to existing indicators and metrics within our products, such as the provision of additional datapoints and meta data (tickbox criteria, citations, analyst comments, collection date, estimated vs reported information etc.); 

- Create and maintain internal and external research guidance documents for indicators and metrics; 

- Propose and enact revisions to indicators and metrics in order to support automation; 
- Support testing of the internal and external validity of indicators and metrics including change/impact analyses and portfolio performance analyses; 
- Interpret and communicate testing results; 
- Apply data science techniques and perform statistical analyses to gain insights on indicator & metrics base, using our internal data base and IT systems structures; 
- Coach and mentor junior analysts in the team. 

 
Qualifications: 

At least 3 years' work experience, especially related to ESG, sustainability research and/or finance;
- Degree(s) in a related discipline (Environmental Sciences, Sustainable Development, Finance, Econometrics, Statistics, or related sciences);
- Good knowledge of ESG investment approaches, products, and research methodologies;
- Capacity to derive insights from both qualitative and quantitative data;
- Problem-solving skills to address complex issues and challenges;
- Capacity to tailor communication to different audiences, such as executives, stakeholders, or technical teams;
- Strong MS Excel knowledge including VBA, with experience in Python, R, or other statistical software;
- SQL and PowerBI skills;
- Experience with quantitative analysis, programming, statistics, econometrics, modeling, and/or big data processing is considered an asset;
- Skilled in coordinating with team members and stakeholders to achieve project objective.