About ESG Book

ESG Book is a global leader in sustainability data and technology. Launched in 2018, ESG Book offers a wide range of ESG-related data, analytics and software that are used by many of the world’s largest financial institutions.

Covering more than 50,000 companies, ESG Book’s product includes ESG and climate data, portfolio and company-level scores, and analytics tools. ESG Book’s SaaS data management and disclosure platform provides access to over 190,000 corporate disclosures, enabling companies to disclose to stakeholders in real-time against multiple frameworks.

Headquartered in London, ESG Book operates from key financial hubs globally including Frankfurt, Boston, New York, Delhi, and Tokyo.

ESG Book as a company is built on 3 pillars:

1. Collective Endeavour – we embrace entrepreneurialism and work together to drive new thinking, solutions, and change.
2. Caring Meritocracy – we support people and teams to maximize their potential; individually, collectively, collaboratively.

1. Radical Transparency – we are open, challenging, and constructive for the advancement of our mission.

Our ambition is to support our clients to build a more sustainable economy. Our core values guide our daily actions as we strive to create lasting change. Our open, collaborative culture provides a nurturing environment for personal and professional growth, enabling us to achieve remarkable outcomes for our clients and stakeholders.

The Quality Team

You will be the go-to person for sustainability data quality. You will be responsible for developing and maintaining our data quality framework. You will be performing data analysis and collaborating with database developers to improve collection and storage procedures. You are passionate about data and know the importance of data quality. Your responsibilities will include:

· Develop and implement data governance policies

· Design and implement data quality control tests

· Develop data quality metrics and monitor performance

· Develop processes and tools to monitor and analyze data quality

· Analyze data sources to identify discrepancies, patterns and trends

· Identify root causes of data quality issues and work with stakeholders to resolve them

· Train staff on data quality policies and procedures