Junior Quantitative Researcher – Options Intelligence

About the Company

We are developing an AI-native investment platform that converts institutional-level market data into smart, accessible products aimed at everyday investors. Our goal is to empower investors with a deeper understanding of global financial markets by leveraging data, research, and AI-driven insights. Our solutions go beyond traditional charts or dashboards, focusing on clear explanations of market dynamics and options market pricing.

Role Overview

We seek a motivated and inquisitive quantitative researcher passionate about translating research into impactful products. The successful candidate will explore financial markets, design Python-based analytical tools, and contribute to products that inform investors worldwide.

Key Responsibilities

• Investigate options markets to uncover insights that can enhance product features.
• Develop intelligence on options metrics including implied volatility, options flow, open interest, dealer positioning, gamma and delta exposure, skew, term structures, earnings, macroeconomic events, and unusual options activity.
• Create research prototypes and analytic tools using Python applied to extensive options datasets.
• Design quantitative indicators, analytics, and AI-driven features facilitating retail investor decision-making.
• Work closely with engineering teams to transition research outputs into production-level products.
• Perform ongoing testing, validation, and iteration of ideas based on data analysis, experiments, and user inputs.
• Compose clear, accessible narratives that simplify complex options markets for investors.

Candidate Qualifications

• A Master's or PhD degree in Finance, Financial Engineering, Mathematics, Statistics, Computer Science, Physics, or a related quantitative field.
• Between 2 and 5 years of professional experience in quantitative research, derivatives, or options analytics.
• Strong grasp of options pricing concepts, including Greeks, implied volatility, dealer hedging strategies, and market microstructure.
• Proficiency in developing analytical tools and prototypes in Python.
• Excellent analytical reasoning, problem-solving abilities, and effective written communication skills.
• A proactive, curious mindset excited to create products actively used by investors.

Preferred Additional Skills

• Experience working with OPRA or institutional options datasets.
• Background in market making, proprietary trading, or sell-side derivatives research.
• Previous involvement in building financial products.
• Familiarity with programming in C++, Rust, or Go.

Projects You'll Lead

You will contribute to building an advanced options intelligence platform that transforms institutional market data into actionable, comprehensible insights tailored for individual investors. Unlike mere charting tools, this platform will elucidate market movements and interpret anticipated options market signals.