Data Science for social finance analysts

Data availability and data quality have increased substantially over the last decade. Better data has led to financial instruments which link impact-related data to financial cash flows. Data is also central to the impact assessment of investments. It is likely that the importance of data will continue to increase with new developments in machine learning and decentralized finance and their implementation in the social finance area.

This workshop will cover how social finance analyst can use tools beyond spreadsheets to analyse bigger dataset and generate better results.

The first part of the workshop will introduce participants to the central areas of data science covering statistical concepts and analytical approaches. Wolfgang Spiess-Knafl will also cover the availability of data and which sources are most promising for social finance analysts. There are open-source data sets which can be accessed easily.

Vincent Lang'at will introduce the participants to the tools which are relevant for social finance analysts. Participants will receive a dataset and will be instructed how to analyse the data for social finance purposes.


Vincent Lang'at has degrees in computer science and management and is currently working as a senior data scientist. He has been involved in various impact-related projects and has helped an impact fund to set up a fully digital impact management tool.

Wolfgang Spiess-Knafl works at the European Center for Social Finance, which delivers EaSI Technical Assistance services on behalf of the European Commission. He has an engineering background and started his career in investment banking. Wolfgang is active in the field of social finance since 2009. His current main interests are emerging new technologies and their intersection with social and environmental objectives.

Practical information

Date: May 16, 10:00 – 14:00 CET

Address: Online