Live opening · Posted 9 hours ago

Head of Quantitative Research & Algorithmic Engineering

Univest · Gurugram, Haryana, India (On-site)
Linkedin No
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At a glance

The key details from the original listing.

Posted 9 hours ago
CompanyUnivest
LocationGurugram, Haryana, India (On-site)
Work modeNo
SkillsPython, C++
SourceLinkedin
ListedPosted 9 hours ago

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About the role

Description supplied by the original job listing.

Role Overview
Univest is seeking a Head of Quantitative Research & Algorithmic Engineering to architect, build, and scale our next-generation automated trading and wealth management infrastructure. In this role, you will lead the end-to-end lifecycle of systematic strategies in Indian derivatives (NSE Equities, Index & Stock Options/Futures)—from mathematical model design and backtesting to building low-latency, production-grade Python/C++ execution engines and broker API integrations.
Key Responsibilities
Strategy Research & Quantitative Modeling:
Design, validate, and deploy high-alpha systematic strategies (options arbitrage, dynamic delta-hedging, mean-reversion, trend-following, and statistical arbitrage) for Indian F&O markets.
Model volatility surfaces, Option Greeks, order-book dynamics, and market microstructure to build robust edge cases.
Conduct rigorous backtesting, walk-forward validation, and stress-testing (Probability of Backtest Overfitting, Monte Carlo simulations) to eliminate curve-fitting.
Algorithmic Execution & Infrastructure Engineering:
Architect and program scalable, cloud-native server-side execution systems in Python and C++ interfacing with broker APIs, OMS/EMS, and FIX protocols.
Optimize execution algorithms to minimize market impact, slippage, and latencies across multi-broker retail setups.
Build automated pre-trade and post-trade risk management engines handling real-time position limits, dynamic margin utilization, and drawdown controls.
Leadership & Scale:
Own the strategy deployment roadmap across retail and high-net-worth portfolio tiers.
Oversee data pipelines (tick-level/L2/L3 order book data), infrastructure, and strategy monitoring systems.
Requirements
Quantitative Depth: Proven mastery of option pricing models (Black-Scholes, IV surfaces), stochastic calculus, statistical arbitrage, and risk metrics (VaR, Sharpe/Sortino, max drawdown controls).
Hands-on Production Code: 100% mandatory expertise in Python and/or modern C++ (C++17/20) for building backend trading engines, data pipelines, and API integrations.
Indian Derivatives Experience: Deep, hands-on experience trading or engineering strategies specifically for NSE Index & Stock Options / Futures (Nifty, BankNifty, Stock Derivatives).
Execution & Microstructure: Practical experience with broker APIs, OMS/EMS architectures, FIX protocol, or low-latency execution routing.

Work arrangement
No

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