Options Quant Researcher (Fintech)

TL;DR

Options Quant Researcher (Python/TradFi): Developing a unified options quoting and pricing engine with an accent on relative-value views on implied volatility and volatility surface calibration. Focus on building fully automated MFT strategies, designing robust signal research pipelines, and optimizing risk-adjusted performance (Sharpe > 2).

Location: Remote (Global)

Company

Proprietary algorithmic trading firm specializing in HFT and MFT across a broad range of asset classes.

What you will do

• Own end-to-end options strategy research from hypothesis and modeling to production and live monitoring.
• Develop a unified options quoting/pricing engine focusing on relative-value views on implied volatility.
• Build and calibrate arbitrage-free volatility surfaces (SVI/SSVI) using realistic market data.
• Translate strategy outputs into execution by routing target delta-orders to minimize Greek risk.
• Design signal research pipelines including feature engineering, labeling, and regime analysis.
• Develop backtests and live-simulation frameworks accounting for slippage, spreads, and market impact.

Requirements

• Proficiency in Python with NumPy, pandas, matplotlib, and SciPy.
• Hands-on experience developing Relative Value strategies in TradFi systematic trading.
• Strong knowledge of options mathematics and intuitive understanding of options.
• Experience with research engineering, clean code, and production readiness.
• Familiarity with quant tooling such as QuantLib.
• Work remotely from anywhere in the world.

Nice to have

• Experience with execution-aware modeling or collaboration with low-latency (HFT) teams.
• Practical application of ML/DL using PyTorch, TensorFlow, or LightGBM.
• Experience with exchange-margined derivatives (NSE, CME, Eurex) and SPAN-style margining.
• Direct experience in cross-instrument arbitrage (spot/futures/options).

Culture & Benefits

• 100% remote organization with a flexible schedule.
• Modern international environment without corporate bureaucracy.
• Excellent opportunities for professional growth and self-realization.
• Compensation for health insurance, sports activities, and non-professional training.