About the Role
The ideal candidate will be highly motivated to work in a dynamic environment that requires self-management of tasks and duties and a high degree of entrepreneurial drive.
Candidates joining our quantitative research division have strong backgrounds in finance, mathematics or a related field and possess good working knowledge of either python or R.
Our internships are mainly remote, and we accept applications from the EU economic area only.
Applicants undergo three interviews with the founding team and a member of their division to assess motivation for the role, technical skills and answer any outstanding questions.
Please submit your application via e-mail, containing your CV and Letter of Motivation.
Requirements
We are looking for the below characteristics in applicants seeking to work in our quantitative research unit:
Good working knowledge of Python or R (both is a plus)
Creative problem-solving and outside the box thinking is highly appreciated
Familiarity with at least 3 relevant quantitative finance and machine learning packages including TTR, Quantmod, PortfolioAnalytics, PerformanceAnalytics, QuantLib, Quandl, Numpy, statsmodel, Pyfolio, Tensorflow, Keras
Good working knowledge in accessing APIs
Ability to analyze both unstructured and structured data
Familiarity with at least one of the following focus areas of forecasting, asset pricing, NLP, automation, backtesting
Ability to work hypothesis driven and in a highly structured manner
Fluent in English (written and spoken), German is a plus but not required
About the Company
Deep Alpha Research is a quantitative investment research firm focusing on alpha factor research, trade strategy creation and portfolio optimization for both retail and institutional clients.
Our team shares a passion for investing, with the right mix of curiosity and creativity to solve some of the most complex challenges in finance.
We are a young, dynamic company that aims to challenge the status-quo of the industry and combines deep-rooted expertise in technology, machine learning, data acquisition and curation with trading.