Quantitative Analyst

Position Summary

We are seeking a highly motivated and analytical Quant Analyst to join Futures First. The role involves supporting development and execution of quantitative strategies across financial markets.

Job Profile

1. 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).

1. 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.

1. 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.

1. 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.

Integrate Bloomberg/Refinitiv APIs for real-time data feeds.

Requirements

Education Qualifications

• B.Tech

Work Experience

• 0-3 years

Skill Set

• Must have: Strong grasp of probability theory, stochastic calculus (Ito’s Lemma, SDEs), and time-series econometrics (ARIMA, VAR, GARCH).
• Must have: Expertise in linear algebra (PCA, eigenvalue decomposition), numerical methods (Monte Carlo, PDE solvers), and optimization techniques.
• Preferred: Knowledge of Bayesian statistics, Markov Chain Monte Carlo (MCMC), and machine learning (supervised/unsupervised learning)
• Libraries: NumPy, Pandas, statsmodels, scikit-learn, arch (GARCH models).
• Back testing: Backtrader, Zipline, or custom event-driven frameworks.
• Data handling: SQL, Dask (for large datasets).
• Power Query, pivot tables, Bloomberg Excel functions (BDP, BDH).
• VBA scripting for various tools and automation.
• Experience with C++/Java (low-latency systems), QuantLib (fixed income pricing), or R (statistical l).
• Yield curve modelling (Nelson-Siegel, Svensson), duration/convexity, OIS pricing.
• Credit spreads, CDS pricing, and bond-CDS basis arbitrage.
• Familiarity with VaR, CVaR, stress testing, and liquidity risk metrics.
• Understanding of CCIL, NDS-OM (Indian market infrastructure).
• Ability to translate intuition and patterns into quant models.
• Strong problem-solving and communication skills (must explain complex models to non-quants).
• Comfortable working in a fast-paced work environment.

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