Academy of Data Science in Finance

For the Dissemination of Expertise and Knowledge in Data Science within the Finance Community



Academy of Data Science in Finance - Agenda

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:

[QAM]
Quantitative Asset Management

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.

[TSA]
Text Mining & Sentiment Analysis

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.

[CRA]
Credit Risk Analytics

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.

Conferences and Events

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:

Industry Forums

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.



Data Science in Finance with R

The DSF-R is the annual conference and main event of our society. At this formal, single-track conference we focus on application driven research done in the high-level statistical programming language R. We encourage research from academia, and the industry.


DSF Meetings

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.



Members and Supporters

Executive Board

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


PD Dr. Ronald Hochreiter

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


Dr. Alexander Eisl

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


Christian Ochs, MSc

General Secretary

COO

WU Vienna [2013-]

Institute for Statistics and Mathematics
Research Associate


KPMG [2012-2013]

Data Scientist


Florian Schwendinger, MSc

Technical Officer

CIO

WU Vienna Research Institute for Capital Markets [2013-]

Research Associate


WU Vienna [2012-2013]

Institute for Statistics and Mathematics
Research Associate


Stephan Kranner, MSc

Treasurer

CFO

DSF Academy e.V.
Scheimpfluggasse 1/15
1190, Wien, Österreich