Head of Quantitative Derivatives Research

Company: Miracles Fintech

Location: Ahmedabad, Gujarat, India

Department: Quantitative Research

Employment Type: Full-Time

About Miracles Fintech

Miracles Fintech is a technology-driven proprietary trading and research firm focused on building scalable, high-performance quantitative trading systems. We operate across Indian financial markets including NSE, BSE, and MCX, with a strong emphasis on scientific research, data-driven modeling, and systematic strategy development.

Our infrastructure includes direct exchange connectivity, tick-level data access, and tightly integrated research-to-production pipelines.

Role Overview

Miracles Fintech is seeking a Head of Quantitative Derivatives Research with a strong mathematical and modeling foundation to lead our derivatives research initiatives.

This role is centered on rigorous quantitative modeling of derivatives markets, with a focus on volatility dynamics, stochastic processes, and statistically robust alpha generation. The position is research-first in nature, emphasizing mathematical depth, empirical validation, and systematic implementation.

The successful candidate will build and lead a dedicated derivatives research team, define modeling standards, and develop production-grade systematic strategies grounded in quantitative theory.

Core Research Mandate

The role will focus on:

• Developing mathematically rigorous models for derivatives pricing and forecasting.
• Researching and modeling implied volatility surface dynamics across strikes and expiries.
• Studying structural inefficiencies in index and stock derivatives markets.
• Modeling:
• Volatility clustering and persistence
• Skew and smile dynamics
• Term-structure evolution
• Intraday volatility microstructure
• Designing and implementing numerical pricing methods including:
• Monte Carlo simulation
• Finite difference methods
• PDE-based solvers
• Stochastic volatility models (Heston, SABR, Local Volatility)
• Building statistically robust backtesting systems capable of handling full option chains and tick-level data.
• Translating theoretical research into systematic, production-grade derivatives strategies.

Key Responsibilities

• Define and drive the firms derivatives research roadmap.
• Lead hypothesis-driven research using sound mathematical reasoning.
• Establish best practices for:
• Model calibration
• Statistical validation
• Robustness testing
• Out-of-sample verification
• Ensure all strategies are supported by rigorous empirical evidence.
• Collaborate closely with technology teams to convert research models into efficient, scalable production systems.
• Build, mentor, and lead a high-caliber quantitative research team.

Required Expertise

Mathematical & Quantitative Foundations

• Strong foundation in probability theory and stochastic calculus.
• Deep understanding of risk-neutral pricing frameworks.
• Experience working with stochastic differential equations.
• Advanced knowledge of time-series modeling and statistical inference.
• Strong analytical and theoretical problem-solving ability.

Derivatives Modeling

• Experience implementing and calibrating:
• Black-Scholes and model extensions
• Local volatility models
• Stochastic volatility models
• Jump-diffusion or regime-switching models
• Deep understanding of implied volatility surfaces and Greeks from a mathematical perspective.
• Familiarity with derivatives market microstructure.

Programming & Numerical Skills

• Strong proficiency in Python (NumPy, SciPy, Pandas).
• Experience implementing numerical methods efficiently.
• Ability to optimize large-scale computations.
• C++ experience preferred for performance-critical modeling.
• Experience working with large historical and tick-level datasets.

Research Philosophy

We value scientific rigor, mathematical depth, and disciplined empirical testing.

All strategies must be grounded in:

• Sound quantitative theory
• Statistically significant results
• Robust validation methodologies

This role is ideal for researchers who enjoy deep mathematical modeling, structured problem-solving, and building systematic frameworks rather than discretionary trading.

Education

PhD or Masters or Bechlor degree in:

• Mathematics
• Statistics
• Physics
• Quantitative Finance
• Engineering (with strong mathematical background)

Strong academic grounding in stochastic processes and advanced probability theory preferred.

What Makes This Role Compelling

• Direct access to exchange-level data and technology infrastructure.
• Opportunity to architect a derivatives research function from the ground up.
• Research-driven culture with strong emphasis on quantitative rigor.
• Competitive compensation aligned with experience and research capability.
• Long-term leadership opportunity within a growing quantitative trading firm.

Application

Interested candidates may apply to:

hradmin@miraclesfintech.com

Website: www.miraclesfintech.com