Quantitative Options Researcher

3 days ago

Singapore J&D Tech Full time

Company

J&D Tech

Designation

Quantitative Options Researcher

Date Listed

08 Aug 2025

Job Type

Entry Level / Junior Executive, Experienced / Senior Executive
- Full/PermPart/TempIntern/TS

Job Period

Immediate Start, For At Least 6 Months

Profession

Banking / Finance

Industry

Finance

Location Name

120 Lower Delta Road, Singapore
- Work from Home

Address

120 Lower Delta Rd, Singapore 169208

Map

Allowance / Remuneration

$800 - 2,000 monthly

Company Profile

We are a highly agile, AI-first quantitative trading firm built on the belief that speed, domain expertise, and creative research edge can outperform legacy players.
- We trade US equity and options markets, focusing on alpha discovery, short-term inefficiencies, and intelligent automation.
- Our infrastructure is powered by a custom-built C++ backtesting engine, with AI-driven multi-agent systems that work 24/7 to generate and refine strategies.
- With a strong track record of consistent profitability and rapid innovation, we operate at the intersection of quant research, machine learning, and high-performance computing.
- We value autonomy, intellectual curiosity, and measurable impact. If you're obsessed with options and love finding edge in noisy markets, we want to hear from you.

**Job Description**:
We’re looking for a highly analytical and driven Options Researcher to join our fast-growing quant trading firm. Your primary responsibility will be to research, prototype, and validate systematic options trading strategies — across intraday, swing, and 0DTE horizons. You’ll work closely with our core team to convert data into edge, and edge into alpha.

This is a hands-on, research-heavy role suited for someone passionate about market microstructure, volatility modeling, and options-based strategy development. You’ll be empowered to test hypotheses quickly, use real-world trade logs to refine strategies, and build robust statistical frameworks to evaluate performance.
- Responsibilities
- Design, research, and backtest quantitative options strategies (including volatility arbitrage, relative value, spread-based, and directional setups).
- Work with raw historical and real-time data (e.g., option chains, implied volatility, Greeks, open interest).
- Identify edge through data exploration, hypothesis testing, and statistical modeling.
- Build and validate predictive features using options and underlying market data.
- Collaborate with execution and data engineering teams to translate research into production-ready models.
- Monitor live strategies, analyze performance, and iterate for robustness.
- Develop tooling for strategy simulation, risk evaluation, and capital optimization.
- Requirements
- Solid background in statistics, financial engineering, mathematics, or computer science.
- Experience with systematic options trading — directional or non-directional (vol/IV, spreads, 0DTE, etc.).
- Strong coding skills (Python required; C++/Rust a plus).
- Familiarity with options data structure (IV surface, Greeks, OI, etc.) and volatility modeling (e.g., GARCH, SABR, local vol).
- Prior experience using backtesting frameworks or developing custom ones.
- Comfort working in a fast-paced, research-oriented environment with a focus on execution.
- Bonus: exposure to machine learning methods for options signal generation.

Application Instructions

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