Senior Quant Researcher

Our Client

Our client is building a new category-defining trading platform — a single app to discover, understand, and trade real-time trends. By fusing perpetual futures with real-time attention data from major social platforms, they are enabling users to measure and trade cultural mindshare at scale. It’s an ambitious and complex product, rethinking how attention can become an asset and how financial products can feel as intuitive and engaging as consumer apps.

About the Team

• A tight-knit team of six full-time employees, all based in New York City

• Fully in-person: engineers, designers, and product minds all work side-by-side

• Everyone contributes directly to shipping product, shaping vision, and learning from users

Core Values

• Invent, Don’t Optimize: The team is focused on first-principles thinking to build something entirely new — not just a better version of what already exists.

• Products That Teach People What They Want: The most powerful ideas often feel inevitable in hindsight. This team is betting on its ability to see around corners.

• No Passengers: Everyone is an owner. No layers, no handoffs. Fast execution, high trust, full commitment — all in one room

The Role: Quantitative Researcher

The team is seeking a highly analytical quantitative researcher with a strong background in market microstructure and statistical modeling. This person will be responsible for researching, designing, and implementing Python-based market-making strategies. They’ll work closely with engineering, product, and design teams to improve performance and evolve the mechanism design behind the protocol.

Key Responsibilities

• Design, simulate, and optimize market-making strategies for perpetual futures

• Model complex financial instruments and their interactions under various market conditions

• Conduct deep statistical analysis and time-series research to inform decision-making

• Collaborate cross-functionally to improve vault design and risk-adjusted performance

• Contribute to internal research infrastructure and tooling

Must-Have Qualifications

• 3+ years of professional experience in quantitative finance, preferably in high-frequency or algorithmic trading

• Deep expertise in Python for numerical programming, data science, and modeling

• Strong background in statistical methods: regression, time-series analysis, optimization, Bayesian networks, decision trees, etc.

• Experience handling and analyzing large, complex datasets

• Strong understanding of market microstructure and automated market making strategies

• Clear and efficient communicator, capable of explaining complex ideas to technical and non-technical collaborators

Nice-to-Haves

• Familiarity with C++ or Rust for performance-sensitive environments

• Experience with exotic options, AMMs, perpetual futures, and DeFi instruments

• MEV searcher experience or a deep understanding of on-chain arbitrage opportunities

• Knowledge of latency optimization and high-performance trading infrastructure

Tech Stack

• Design: Figma

• Frontend: React (TypeScript), TailwindCSS, Vite

• Backend: Rust, Java

• Research: Python, PyTorch

• Infrastructure: AWS, Cloudflare

• Smart Contracts: Solidity, Foundry, Slither

Interview Process

1. Intro & Behavioral Call – 45-minute conversation with a founder

2. Technical Virtual Onsite – Includes a live coding challenge and system design discussion

3. Reference Checks – 2–3 professional references from past supervisors

4. Compensation Review – 30-minute offer walkthrough with a founder

Compensation

The compensation package includes a competitive base salary and significant equity upside. All equity grants follow a standard four-year vesting schedule aligned with the founding team.