Astant Global Management

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. We are looking for a Quantitative Analyst to design, implement, and maintain the analytical backbone of OpenMacro’s dynamic strategies and portfolio simulations. This role will bridge market research, data science, and risk modeling to deliver actionable, data-driven insights for our users. 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.