About us
At RavenPack, we are at the forefront of developing the next generation of generative AI tools for the finance industry and beyond.
With 20 years of experience as a leading big data analytics provider for financial services, we empower our clients—including some of the world's most successful hedge funds, banks, and asset managers—to enhance returns, reduce risk, and increase efficiency by integrating public information into their models and workflows.
Building on this expertise, we are now launching a new suite of GenAI and SaaS services, designed specifically for financial professionals.
Join a Company that is Powering the Future of Finance with AI
RavenPack has been recognized as the Best Alternative Data Provider by WatersTechnology and has been included in this year's Top 100 Next Unicorns by Viva Technology.
We recently launched Bigdata.Com, a next-generation platform aimed at transforming financial decision-making.
Join RavenPack:
RavenPack is searching for a Senior Quantitative Researcher to join the Data Science - QIS Team at our Spanish headquarters, Marbella.
We offer competitive compensation, active mentoring, exposure to the top trading firms, and a fun working environment.
Relocation assistance is available.
Your Responsibilities:
Identifying, validating, and amplifying predictive signals within our data while discerning and filtering out irrelevant information.
Formulating systematic trading strategies spanning multiple asset classes with a major focus on equities, enriching security-selection capabilities with Alternative Data across different holding periods.
Offering data-driven insights, engaging in discussions about your research, and presenting trading strategies to leading quantitative researchers and portfolio managers in the field.
Effectively communicating intricate analytical concepts to management in a clear and concise manner.
What We're Looking For:
A PhD/MSc in Quantitative or Computational Finance, or from any related fields including Machine Learning, Econometrics, Applied Mathematics, etc.
5+ years of relevant work experience as a quantitative researcher, manipulating large and noisy alternative datasets for feature engineering, signal amplification, and portfolio backtesting.
Outstanding quantitative, analytical, and problem-solving skills, with proven ability to develop original research and hypothesis testing.
Demonstrated proficiency in at least Python and SQL.
Strong enthusiasm for technology, and familiarity with big data technologies coupled with proficiency in machine learning is highly advantageous.
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