The Academy of Data Science in Finance (dsf.academy) is a non-profit initiative. We strive to expand and disseminate the knowledge in Data Science within the Finance Community -- both in Academia and the Industry. Our Agenda is focused around the following working groups:
The new era of asset management has been introduced by AI, Machine and Deep Learning approaches, genetic algorithms and the availability of computational power on demand. We want to show you how to take part in this development.
Information is often contained in textual statements and may be hidden between the lines. Our objective is to help you to identify important information and capture sentiment in financial markets.
Regardless of big data availability, relevant information for credit risk analytics is still sparse. We want to motivate, how algorithms can learn from small training sets and become your smart solution for risk detection.
The Academy of Data Science in Finance is hosting a series of events every year. As a member of our society, you have access to these events and receive special participation rates. Please find more information on our activities and events below:
At our quarterly forums we discuss state-of-the art methods, and advances in theory or challenges in the financial industry. Furthermore, participants may contribute to the Agenda of the DSF Academy and decide on future discussion topics.
The DSF-R is the annual conference and main event of our society. The conference aims to bring academics and finance professionals together to discuss all applications of contemporary Data Science approaches to the area of Finance. These topics include Machine Learning, Deep Learning, Artificial Intelligence, Sentiment Analysis and Prescriptive Analytics.
Our monthly meetings offer the opportunity to exchange knowledge and expertise among people from academia and the industry. In an after-work athmosphere, we are hosting short impulse presentations on data science applications.
The Academy of Data Science in Finance was founded in 2017 by Researchers from Computational Statistics and Finance, as well as Practitioners from the Financial Industry with a common interest in Data Science and problem solving. Currently, the DSF Academy is represented by the following Executive Board:
algorithmic.finance
CEO, Founder
WU Vienna [2009-]
Institute
for Statistics and
Mathematics
Docent,
Principal Investigator
Austrian Society for Operations Research [2013-]
Vice-President
President
CEO
FINcredible
CTO, Co-Founder
WU Vienna [2013-]
Institute
for Finance Banking
and
Insurance
Assistant
Professor
DEXHELPP [2008-]
Decison
Support for Health
Policy and
Planning
Research Partner
Vice-President
Deputy CEO
FINcredible [2017-]
CEO, Co-Founder
WU Vienna [2014-]
Institute
for Finance Banking
and
Insurance
Research
Associate
Finance Alumni Club [2015-]
Chairman of the Board
General Secretary
COO
WU Vienna [2013-]
Institute
for Statistics and
Mathematics
Research
Associate
KPMG [2012-2013]
Data Scientist
Technical Officer
CIO
WU Vienna Research Institute for Capital Markets [2013-]
Research Associate
WU Vienna [2012-2013]
Institute
for Statistics and Mathematics
Research
Associate
Treasurer
CFO
The Academy of Data Science in Finance is supported by an academic advisory board. The advisory board consists of senior experts from areas relevant to the agenda of the DSF Academy.
WU Vienna
Professor of Statistics
Data Science, Computing, Credit Risk
WU Vienna
Professor of Finance
Finance, Banking, Credit Risk
WU Vienna
Professor of Production Management
Industry 4.0, Big Data