About the role

Quantitative Research team at DeepFin Research builds and deploys deep‑learning‑driven high‑frequency trading systems for global options markets. The researcher designs ultra‑fast volatility surface models, develops market‑making and execution algorithms, and creates real‑time hedging frameworks to monetize AI‑generated signals. Bengaluru, Jersey, London, New York – on‑site hybrid model, relocation support available.

What you’ll do

Design and calibrate ultra‑fast volatility surface models
Integrate models into live trading systems
Develop high‑frequency quoting, hedging, and execution algorithms
Backtest systematic intraday options strategies
Build real‑time delta/gamma/vega risk dashboards
Create automated dynamic gamma‑hedging frameworks
Collaborate with quant developers to optimize performance
Analyze market microstructure to improve execution

What you’ll bring

5-7 years quant research or trading experience
Direct high‑frequency options market‑making experience
Strong C++ and Python programming
Experience with vol surface models (SVI, SABR)
Advanced degree in Math, Physics, Statistics, CS or related field
Knowledge of Greeks and options microstructure
Ability to design low‑latency execution and hedging systems
Familiarity with deep learning or reinforcement learning

Skills

C++PythonVol Surface ModelingHigh‑Frequency TradingOptions PricingRisk AnalyticsMachine LearningLow‑Latency Systems