Quantitative Analyst

Company Description

Astant Global Management is a quantitative consulting firm specializing in advanced portfolio analytics for institutional and private investors. We combine macroeconomic insight, data science, and proprietary quantitative models to uncover hidden risks and opportunities within portfolios. Our team of macro strategists and quantitative analysts provides independent portfolio diagnostics, predictive analytics, and optimization frameworks to enhance risk-adjusted performance across global markets. With offices in Luxembourg, Madrid, and Bangalore, Astant operates globally to help clients make informed, data-backed investment decisions in an uncertain world.

Overview

Astant is building the next-generation macro-investment platform — blending institutional-grade quantitative analytics with an AI-driven, community-based interface for professional and semi-professional investors.

Quantitative Analyst

Responsibilities

• Develop and maintain quantitative models

  that power OpenMacro’s investment strategies (e.g., Global Macro Tendency, Market-Neutral L/S).
• Conduct

  market risk analysis

  , simulate portfolio behavior, and generate

  predictive indicators

  for macroeconomic factors (growth, inflation, rates, FX, commodities).
• Design and backtest models for

  return, volatility, and risk-adjusted performance

  under different user-defined parameters.
• Calculate and optimize

  risk metrics

  such as Sharpe Ratio, Sortino, Value-at-Risk (VaR), and Maximum Drawdown.
• Collaborate with the

  Data Engineer and Full Stack Developer

  to deploy quantitative models as scalable API endpoints.
• Partner with the

  AI team

  to translate model outputs into human-readable summaries for the dashboard and strategy pages.
• Research and integrate external data sources (FRED, Quandl, IMF, Yahoo Finance, etc.) to support dynamic macro modeling.
• Continuously validate model performance and ensure alignment with institutional limits and user-defined risk tolerances.

Qualifications

• Strong background in

  quantitative finance, econometrics, or applied mathematics

  .
• Deep understanding of

  market risk concepts, portfolio theory, and factor modeling

  .
• Proven ability to perform

  time-series and cross-sectional analysis

  using statistical tools.
• Proficiency in

  Python

  (NumPy, pandas, statsmodels, scikit-learn, PyPortfolioOpt).
• Experience with

  financial data APIs

  and data wrangling for large datasets.
• Ability to translate quantitative outputs into

  intuitive insights

  for non-technical users.
• Excellent problem-solving skills, attention to detail, and ability to work autonomously.
• Master’s or PhD in

  Finance, Economics, Applied Mathematics, or a related field

  .
• Experience in a

  macro, multi-asset, or systematic trading context

  is a strong plus.