Macro-Quantitative Strategist

hace 2 semanas

Madrid, Madrid, España Astant Global Management A tiempo completo

OpenMacro
is building the next generation of AI-driven macroeconomic and quantitative intelligence.

We combine econometrics, machine learning, and large-scale financial data to create institutional-grade forecasting models and investment frameworks accessible to professional investors, family offices, and sophisticated retail users.

Role Overview

We are looking for a
Macro-Quantitative Strategist
to lead the development of predictive models linking global macroeconomic variables with financial asset behavior.

The ideal candidate bridges economics, quantitative research, and data science — capable of transforming complex macro signals into actionable, data-driven investment insights.

You will play a key role in building the core modeling infrastructure for OpenMacro's forecasting and strategy layer.

Key Responsibilities

  • Design and implement
    macroeconomic forecasting models
    (e.g., VAR, dynamic factor, Bayesian, and ML-based frameworks).
  • Develop and test
    cross-asset quantitative signals
    derived from macro variables such as growth, inflation, liquidity, money supply, labor markets, and policy conditions.
  • Integrate
    machine learning and econometric methods
    for predictive modeling, regime detection, and scenario analysis.
  • Build automated data pipelines for
    economic and financial time series
    — including cleaning, normalization, feature engineering, and API-based ingestion.
  • Evaluate and document model performance using robust out-of-sample and stress-testing methodologies.
  • Collaborate with engineering teams to
    deploy models into production
    environments and connect forecasts to strategy dashboards and APIs.
  • Contribute to the overall
    investment strategy layer
    by identifying the assets or factors with the highest predictive power.

Requirements

  • Proven experience in
    Global Macro modeling
    — building frameworks that capture macroeconomic linkages across economies, policy cycles, and cross-asset dynamics.
  • Strong understanding of
    macroeconomic theory
    (growth, inflation, liquidity, policy transmission mechanisms) and how it translates into
    market behavior
    .
  • Strong proficiency in
    Python
    (NumPy, pandas, scikit-learn, statsmodels, TensorFlow/PyTorch).
  • Hands-on experience in
    time series modeling, feature extraction, and ML model deployment
    .
  • Ability to work with
    noisy, heterogeneous datasets
    and apply techniques for cleaning, variable selection, and non-linear relationship analysis.
  • Strong analytical and communication skills, with attention to interpretability and transparency.

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