Quantitative Developer - Python

Job seeking a highly skilled and intellectually curious Quantitative Researcher to develop sophisticated models and trading strategies that drive our portfolio optimization, hedging techniques, and income generation initiatives. This role is ideal for someone with a deep understanding of quantitative finance and a passion for building systems that convert complex data into actionable, real-world outcomes. Youll work on high-impact financial problemsdesigning algorithms that exploit volatility, time decay, and market inefficiencies to generate sustainable alpha. Collaboration with data engineers, AI specialists, and product teams will be central to your success in transforming insights into robust, production-grade solutions. Key Responsibilities : - Design and develop quantitative models for portfolio optimization and hedging strategies across multiple asset classes. - Create trading strategies that leverage time decay and volatility-based approaches to produce consistent returns. - Backtest, evaluate, and refine models using historical and real-time market data to ensure performance, stability, and risk mitigation. - Partner with data engineers to process, clean, and integrate high-frequency and alternative data sources for alpha discovery. - Analyze model behavior under different market conditions and adapt algorithms accordingly. - Contribute to the continuous improvement of research frameworks, trading systems, and infrastructure. - Let rigorous quantitative analysis guide every model and strategy design. - Commit to continuous testing, iteration, and refinement of algorithms for enhanced performance and robustness. - Build financial models that support Hushhs mission of creating long-term, sustainable value in dynamic markets. Required Skills and Qualifications : - 5 years of experience in quantitative finance, algorithmic trading, portfolio optimization, or related fields. - Strong programming skills in Python, with expertise in libraries such as NumPy, Pandas, SciPy, and statsmodels. - Deep knowledge of derivatives, especially options pricing, Greeks, time decay, and implied volatility surfaces. - Familiarity with risk management principles, including drawdown control, VaR, and scenario analysis. - Experience with backtesting tools, performance attribution, and optimization algorithms. - Proven ability to design models that balance return generation with risk control in real-world financial environments. - Experience with machine learning, alternative data, or reinforcement learning techniques in trading contexts. (ref:hirist.tech)

Location: in, IN

Posted Date: 5/1/2025