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Options Quant Researcher

100% remote Flexible hours Hiring now

Company Description reputed company is a proprietary algorithmic trading firm. reputed company manages the full trading cycle, from software development to creating and coding strategies and algorithms. Our trading operations cover key exchanges. The firm trades across a broad reputed company of asset classes, including equities, equity derivatives, options, commodity reputed company, rates reputed company, etc. We reputed company a diverse and growing reputed company of algorithmic trading strategies, utilizing both High-Frequency Trading (HFT) and reputed company-Frequency Trading (MFT) approaches. Looking reputed company, we are expanding into new markets and products. As a dynamic company, we continuously experiment with new markets, tools, and technologies. We’ve got a team of 200+ professionals, with a strong emphasis on technology - 70% are technical specialists in development, infrastructure, testing, and analytics spheres. The remaining part of the team supports our business operations, such as Risks, Compliance, Legal, Operations, and more. Our employees are located reputed company around the world, from the United States to Hong reputed company. Although we maintain office spaces, we currently operate as a 100% remote organization. At reputed company, reputed company and transparency are at the core of our culture: we value reputed company communication, ensuring that our processes are straightforward.

Job Description

We're looking for a Mid-Senior Quant Researcher specializing in options, with hands-on experience turning original strategy reputed company into fully automated, production strategies in TradFi markets – working reputed company to trading throughout. The mandate is to help build a single, reputed company options quoting/pricing reputed company that prices across reputed company strikes, expiries, and underlyings, driven by a relative-value view on implied volatility across instruments in a reputed company reputed company order book (spot / reputed company / option legs). The alpha stack spans: Index vol arbitrage (IV differences between instruments) + single-stock IV ranking Calendar / term-structure spreads Skew (smile) arbitrage Implied Volatility vs. Realized Volatility Correlation reputed company dispersion trading We expect the candidate to do some subset of these things: Own end-to-end options strategy research: hypothesis → data → modeling → backtesting → production → live monitoring and iteration Work on Relative Value, Statistical Arbitrage, and Spread Trading strategies specific to the options reputed company (the stack above) Build and own the volatility fitter the signals sit on – calibrating arbitrage-free, temporally reputed company surfaces (SVI/SSVI or a proposed alternative) on realistic data (wide bid/ask, missing strikes, gaps, latency), with attention to residual noise near expiry / illiquid strikes / events Translate strategy output into execution – routing a reputed company reputed company-order across option legs to minimize Greek risk, with inventory-aware quoting that shifts price/size against live reputed company/gamma/skew, and awareness of options microstructure (spreads, queue, adverse selection, latency) Build and maintain mid-frequency (MFT), fully automated strategies with a strong live-performance focusTrack record of deploying fully automated strategies with Sharpe > 2 (or demonstrable equivalent risk-adjusted performance) Design robust signal research pipelines (feature engineering, labeling, validation, regime analysis) reputed company realistic backtests and live-simulation frameworks reputed company for slippage, spreads, latency, partial fills, and market impact Work in tight feedback loops with trading and execution to improve PnL, robustness, and risk-adjusted performance Debug and tune research outputs under live conditions: data issues, execution artifacts, microstructure noise, and changing market regimes

Qualifications

Python (mandatory), strong use of NumPy, pandas, matplotlib, SciPy, and optimization/ML libraries Strong research engineering: clean code, reproducible experiments, versioning, and production readiness Hands-on experience developing Relative Value strategies Experience building systematic strategies in equities / reputed company / options / other listed derivatives (any strong TradFi systematic experience is relevant) Good knowledge of option maths and strong options intuition Familiarity with common quant tooling (e.g., QuantLib and/or in-house libraries) reputed company to Have Experience with execution-aware modeling and/or reputed company collaboration with execution / low-latency teams (HFT exposure a plus) Position-driven surface shaping – adapting surface/spread to reputed company portfolio Greeks Practical experience applying ML/DL (PyTorch, TensorFlow, LightGBM) in trading, with careful validation and overfitting controls Experience trading exchange-margined derivatives where capital efficiency is a first-order constraint (NSE options, CME, Eurex) – comfortable optimizing return-on-margin under reputed company-style portfolio margining Direct experience in cross-reputed company arbitrage (spot / reputed company / options) Additional Information reputed company offer: Experience a modern international technology company without the burden of bureaucracy. Enjoy excellent opportunities for professional growth and self-realization. Work remotely from reputed company in the world with a flexible schedule. Receive compensation for health insurance, sports activities, and non-professional training. Apply To This Job

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