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 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:
As a Senior Quant Researcher, you will join the 'Quantitative Investment Strategies (QIS) Team,' consisting of four quant researchers dedicated to feature engineering and developing systematic trading strategies.
Your work will primarily involve bottom-up research, with some top-down research opportunities.
You will create white papers to enhance RavenPack's reputation as a thought leader in the alternative data industry and present trading strategies to quantitative analysts.
You will independently work on practical use cases that demonstrate the value of RavenPack data.
Additionally, your responsibilities will include:
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 features engineering, signal amplification, and portfolio backtesting.
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