Position Overview

We are establishing and scaling a next-generation investment unit focused on Options Trading, Quantitative
Analysis, Advanced Risk Management, and the integration of cutting-edge Artificial Intelligence technologies.
In line with this vision, we are seeking a highly analytical, creative, and builder-minded Senior Options Trader.
The ideal candidate will possess a deep intuitive grasp of financial markets and option structures, combined
with the ability to leverage AI tools and data analytics to generate a sustainable competitive edge. This
position is not merely a traditional execution role; it is a strategic opportunity to participate in designing,
architecting, and developing an algorithmic investment framework from the ground up to institutional scale.

Core Mission

Design, optimize, and execute advanced options trading strategies to achieve:

• Optimal, consistent risk-adjusted returns (Alpha generation).
• A sustainable edge through advanced data modeling and AI implementation.
• Scalable, institutional-grade research and trading infrastructure.

Key Responsibilities

1. Options Trading & Structuring

• • Design, backtest, and execute complex, multi-leg options strategies, including:
    • Vertical Spreads, Iron Condors, Calendar Spreads, Ratio Backspreads
    • Straddles, Strangles, Covered Calls, Cash Secured Puts
  • Develop and deploy Volatility Strategies, specializing in Implied Volatility (IV) Skew/Smile dynamics and statistical arbitrage.
  • Monitors order flow, block trades, and structural market imbalances to capture mispricings.

     2. Quantitative R&D & Strategy Validation

• • Build and implement robust Backtesting and Stress Testing frameworks to evaluate strategy resilience across diverse market regimes.
  • Analyze historical market datasets to uncover high-probability (Win Rate) setups and non-linear patterns.

     3. Financial AI & Machine Learning

• • Utilize Machine Learning and Deep Learning models for volatility forecasting, regime detection, and price behavior analysis.
  • Leverage advanced generative AI tools to automate research pipelines, synthesize unstructured financial data, and optimize decision-making workflows.
  • Develop quantitative decision-support systems and intelligent performance analytics.

     4. Dynamic Portfolio Risk Management

• • Actively manage, hedge, and monitor portfolio Greeks (Delta, Gamma, Theta, Vega, Rho) in real-time.
  • Establish dynamic capital allocation constraints, drawdown limits, and trailing risk thresholds.
  • Generate comprehensive P&L attribution and risk matrix reports for senior leadership.

Qualifications & Skills

• Minimum of 5 years of live, verifiable experience in options trading (experience in international derivatives/options markets is highly advantageous).
• A proven, documented Track Record of designing and managing complex options portfolios.

• Mastery of options pricing theory, the Black-Scholes model, binomial models, and volatility dynamics.
• Deep understanding of portfolio risk mechanics, leverage, and margin management.
• An advanced degree (Master's or Ph.D.) in Financial Engineering, Quantitative Finance, Mathematics, Statistics, or Computer Science is preferred.

• Proficiency in Python and its core data science stack (*Pandas, NumPy*).
• Hands-on experience with Machine Learning libraries (*Scikit-Learn, TensorFlow, PyTorch*) and quantitative libraries (*QuantLib*).

• Practical experience integrating AI tools into analytics, software development, or data extraction.
• Strong algorithmic thinking with the ability to translate qualitative market views into quantitative, datadriven code.

• Exceptional analytical, structural, and data-centric mindset.
• High psychological resilience and the capacity to make rational decisions under intense market pressure and volatility.
• Entrepreneurial & Builder Mindset: A strong desire to construct infrastructure from ground zero and scale it.