Quantitative Software Engineer

Financial Services company
Vienna, Austria
Roles:
Machine Learning
Must-have skills:
PyTorchPython
Considering candidates from:
Austria
Work arrangement: Onsite
Industry: Financial Services
Language: English
Level: Middle or senior
Required experience: 2+ years
Relocation: Paid
Visa support: Provided
Size: 11 - 50 employees

Quantitative Software Engineer

Financial Services company
Vienna, Austria
Our client is a technology-led hedge fund founded in 2015, passionate about collecting, cleaning, transforming, and storing data to feed trading strategies. Its data driven trading models utilize a variety of open-source technologies and multiple data sources, from vendor APIs to fleet of web crawlers running 24/7, to make trading decisions in the global markets. The firm manages assets on behalf of a diverse range of clients including pension plans, insurance companies, financial institutions, family offices, qualified individual investors, among others.
Tasks:
  • Design for the evolving scale and scope of the company's quantitative research program
  • Build high-performance platforms for quantitative research
  • Develop, deploy, and monitor models that trade in financial markets
  • Write documentation and conduct code reviews
  • Promote the best coding practices firm-wide
Must-have:
  • Degree in computer science or related field
  • Development experience on AWS or other cloud providers
  • 2+ years of Python experience including with libraries such as Numpy and Pandas
  • Experience with ML
  • Excellent communication skills, self-starter, quick learner, positive attitude, and team player
  • Experience in at least one of the following areas
    • Econometrics, factor analyses, or automated trading
    • Weather data modeling
    • Machine Learning techniques, e.g. neural networks
    • Robotics and/or sensor networks
    • Other high-dimensional, computational heavy data problem spaces
Nice-to-have:
  • Pytorch, and TensorFlow
Interview process:
  1. Intro call with Toughbyte
  2. Call with the Hiring Manager for 30 minutes
  3. Technical interview
  4. Call with the Head of Portfolio and the Head of Trading