About QPIAI India Pvt. Ltd.:

QPIAI India Pvt. Ltd. is a next-generation technology company focused on Artificial Intelligence, Quantum Computing, and advanced IT innovation. At QPIAI, we believe that great ideas grow in the right environment. Our culture is built on flexibility, collaboration, and continuous learning, supported by a strong commitment to employee well-being and work–life balance. We provide a workplace that encourages creativity, fosters professional growth, and empowers people to take ownership of impactful projects.

If you are driven by curiosity, inspired by cutting-edge technologies, and eager to contribute to a global tech journey, QPIAI is the place to grow, lead, and make a meaningful impact.

About the Role:

We are seeking a senior financial expert with deep domain knowledge in derivatives pricing, portfolio optimization, and risk modelling. You will own the full lifecycle of quantitative model development, from problem formulation to production deployment, with exposure to emerging computational paradigms including quantum-inspired methods.

Core Responsibilities

• Design and refine stochastic models for derivative pricing (Black-Scholes, Heston, SABR, local-vol) and push the performance boundaries of Monte Carlo and PDE solvers.
• Architect portfolio optimization frameworks (mean-variance, CVaR, Black-Litterman) and formulate tractable mathematical programs for real-world asset allocation constraints.
• Lead credit risk and counterparty exposure analysis (CVA/DVA/FVA/XVA), stress testing, and scenario generation at scale.
• Build and validate fixed-income analytics; yield curve construction, interest-rate term structure modelling, and prepayment risk engines.
• Own market microstructure analysis and execution cost modelling.

Required Qualifications

• 7+ years in quantitative finance, structuring, or sell-side/buy-side quant research.
• Expert-level proficiency in stochastic calculus, measure-theoretic probability, numerical methods, finite difference techniques, Monte Carlo.
• Production experience with derivatives pricing libraries and risk engines.
• Strong command of Python and at least one compiled language (C++, Rust).
• Knowledge of combinatorial optimization applied to asset allocation or trade execution.
• Familiarity with regulatory capital frameworks (Basel III/IV, FRTB SA/IMA) and market-risk metrics (VaR, ES, Greeks P&L attribution).

Preferred Qualifications

• Awareness of quantum computing and its potential financial applications.
• PhD or equivalent research depth in financial engineering, applied mathematics, or computational physics.
• Publications or applied projects in computational finance.