Overview
In this role you drive the development of systematic trading strategies using RavenPacks alternative data, collaborating with cross-functional teams to showcase data value to traders and investors. You will lead feature engineering and model development within the QIS team, delivering research-driven insights and practical use cases for clients. You'll publish white papers to position RavenPack as a thought leader and present strategy results to quantitative analysts. This hybrid role combines independent research with client-facing impact in a innovation-forward, finance-focused environment.
Compensaciones / Incentivos International culture
Competitive salary
Continuous learning
Innovation culture
Relocation assistance to Marbella
Marbella shuttle bus
Responsabilidades Identify and filter predictive signals in datasets to support better decision-making
Design systematic trading strategies across asset classes, with a focus on equities




Advance feature engineering using analytics products and enriched textual content
Present data-driven research and trading strategies to peers and portfolio managers
Communicate complex analytics concepts clearly to management with actionable insights
Requisitos principales PhD in Quantitative or Computational Finance or related fields including Machine Learning, Econometrics, Applied Mathematics (essential)
Minimum 5 years of experience as a quantitative researcher
Proficiency in Python and SQL
Experience handling large, noisy alternative datasets for feature engineering and backtesting
Strong analytical and problem-solving skills with ability to conduct hypothesis testing
Communication with technical and non-technical stakeholders
Collaborative mindset for cross-team work
Enthusiasm for finance and technology
Python
SQL
Machine Learning

📌 Lead Quantitative Researcher (Málaga)
🏢 Ravenpack
📍 Málaga