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Posted 12 June, 2026

Quantitative Trader

Neo Wealth and Asset Management
Remote Nationwide, IN Full Time
Reference: c90632ed0a4e7073

Job Description

Role: Quant Strategist/Trader Role Summary: We are looking for a Quant Strategist – LFT to lead the research, development, and deployment of systematic trading strategies across equity derivatives, index futures/options, and factor-based equity portfolios . This role is ideal for someone with strong quantitative research capabilities, deep understanding of financial markets, and the technical expertise to translate research into production-ready trading systems. You will work at the intersection of quantitative research, portfolio construction, execution systems, and data infrastructure , with a focus on building scalable low- to mid-frequency strategies.

Key Responsibilities Quantitative Research & Strategy Development Conduct rigorous quantitative research to develop low- to mid-frequency systematic strategies in equity derivatives and cash equities. Study academic literature, market microstructure, and alternative data to generate and test new hypotheses. Design and implement strategies in: -Index Futures -Options (using Greeks, volatility surfaces, liquidity, skew, carry, etc.) -Factor-based long/short equity portfolios Build and evaluate predictive signals using econometric, statistical, and machine learning methods.

Develop robust portfolio construction frameworks, including factor blending, risk budgeting, and optimization. Execution & Production Deployment Translate research strategies into production-grade code for live deployment. Work closely with execution systems to ensure robustness, scalability, and operational efficiency.

Monitor live strategies, identify anomalies, and improve execution performance. Enhance trading systems periodically for latency, stability, and process optimization. Data & Backtesting Infrastructure Maintain and improve proprietary backtesting libraries and research frameworks.

Collaborate with data engineering teams to onboard new datasets and improve internal databases. Ensure data integrity, quality control, and research reproducibility. Optimize simulation frameworks for speed, realism, and scalability.

Required Skills & Qualifications Solid foundation in multi-factor models, alpha research, and portfolio construction Strong understanding of options pricing, derivatives, volatility, and Greeks Advanced knowledge of: -Probability -Statistics / Econometrics -Linear Algebra -Time Series Analysis High proficiency in programming (Python required; C++/Java preferred) Experience with quantitative research and hypothesis-driven strategy development Ability to work with large datasets and production systems Familiarity with fundamental and alternative datasets is a strong plus Preferred Background Experience in systematic trading, quantitative finance, or adjacent research-heavy fields Prior work in: -Equity derivatives -Statistical arbitrage -Factor investing -Quantamental strategies Exposure to live strategy deployment and trading infrastructure

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