Quant Analyst

As a highly motivated and analytical Quant Analyst at Futures First in Gurugram, India, your role involves supporting the development and execution of quantitative strategies across financial markets. Here is a breakdown of your key responsibilities: - Statistical Arbitrage & Strategy Development: - Design and implement pairs, mean-reversion, and relative value strategies in fixed income (govvies, corporate bonds, IRS). - Apply cointegration tests (Engle-Granger, Johansen), Kalman filters, and machine learning techniques for signal generation. - Optimize execution using transaction cost analysis (TCA). - Correlation & Volatility Analysis: - Model dynamic correlations between bonds, rates, and macro variables using PCA, copulas, and rolling regressions. - Forecast yield curve volatility using GARCH, stochastic volatility models, and implied-vol surfaces for swaptions. - Identify regime shifts (e.g., monetary policy impacts) and adjust strategies accordingly. - Seasonality & Pattern Recognition: - Analyse calendar effects (quarter-end rebalancing, liquidity patterns) in sovereign bond futures and repo markets. - Develop time-series models (SARIMA, Fourier transforms) to detect cyclical trends. - Back testing & Automation: - Build Python-based back testing frameworks (Backtrader, Qlib) to validate strategies. - Automate Excel-based reporting (VBA, xlwings) for P&L attribution and risk dashboards. Additionally, you will integrate Bloomberg/Refinitiv APIs for real-time data feeds. Qualifications required for this role include: - Education Qualifications: B.Tech - Work Experience: 0-3 years Your skill set should include: - Strong grasp of probability theory, stochastic calculus (Itos Lemma, SDEs), and time-series econometrics (ARIMA, VAR, GARCH). - Expertise in linear algebra (PCA, eigenvalue decomposition), numerical methods (Monte Carlo, PDE solvers), and optimization techniques. - Knowledge of Bayesian statistics, Markov Chain Monte Carlo (MCMC), and machine learning (supervised/unsupervised learning). - Proficiency with libraries such as NumPy, Pandas, statsmodels, scikit-learn, arch (GARCH models). - Experience with back testing tools like Backtrader, Zipline, or custom event-driven frameworks. - Data handling skills in SQL, Dask (for large datasets), Power Query, pivot tables, and Bloomberg Excel functions. - VBA scripting for automation. - Familiarity with C++/Java, QuantLib, R, yield curve modelling, credit spreads, CDS pricing, VaR, CVaR, stress testing, and liquidity risk metrics. - Understanding of market infrastructure like CCIL, NDS-OM, and the ability to translate intuition and patterns into quant models. - Strong problem-solving and communication skills to explain complex models to non-quants effectively. You will be working in Gurugram with work hours aligned to APAC Markets.,