Quantitative Developer

About the Firm

We are a quantitative, market-neutral digital asset hedge fund focused on systematic alpha generation across CeFi and DeFi markets.

Our strategies span HFT, MFT, basis arbitrage, volatility carry, statistical arbitrage, and hedged DeFi yield, with an uncompromising focus on risk management, capital preservation, and scalable infrastructure.

We operate with an institutional mindsetproduction-grade systems, rigorous research, and disciplined execution.

Role Overview

We are hiring a Quantitative Developer / Quant Trader to design, implement, and operate low-latency, systematic trading strategies across centralized and decentralized crypto markets.

This role sits at the intersection of quant research, execution engineering, and risk-aware portfolio construction.

Required Skills (Non-Negotiable)

1. Coding & Systems Engineering

Go (Primary Production & Execution)

Design low-latency, concurrent systems

Implement OMS, execution engines, and market data handlers

Efficient memory management and profiling

Network programming (WebSocket / streaming APIs)

Lock-free or low-contention data structures

Python (Primary Research & Simulation)

Vectorized numerical computing (NumPy, pandas/polars)

Statistical analysis and signal research

Backtesting and simulation framework development

Data cleaning, feature engineering, and research pipelines

2. Algorithmic Reasoning & Problem Solving

Translate trading ideas into deterministic algorithms

Reason about:

Time and space complexity

Latency vs fill probability trade-offs

Deterministic vs stochastic execution paths

Design state-driven trading logic (event-based systems)

Debug and reason about live trading failures under stress

3. Quantitative Research & Modeling

Develop and validate alpha signals, including:

Mean reversion / momentum

Funding and basis signals

Volatility and regime filters

Time-series analysis:

Stationarity testing

Cointegration

Signal decay and turnover analysis

Portfolio construction with transaction costs

Statistical validation:

Out-of-sample testing

Overfitting control

Parameter sensitivity analysis

4. Mathematics & Statistics

Probability theory

Linear algebra

Optimization techniques

Stochastic processes (basic)

Risk metrics (volatility, drawdown, CVaR)

5. Market Microstructure & Execution

Order book dynamics

Queue position and fill probability

Passive vs aggressive execution logic

Slippage and impact modeling

Exchange-specific behavior and fee structures

6. CeFi & DeFi Trading Knowledge

Spot, perps, futures, options

Funding rate mechanics

AMMs (Uniswap v3, Curve)

Impermanent loss modeling

On-chain execution costs and MEV awareness

7. Backtesting, Risk & Production

Tick-level backtesting with realistic assumptions

Latency, partial fills, and fee modeling

Stress testing and regime shifts

Strategy-level and portfolio-level risk limits

Kill-switches and automated risk controls

8. Infrastructure & Tooling

Linux

Docker / CI-CD

Cloud basics (AWS / GCP)

Monitoring, logging, alerting

Experience Requirements

38+ years in systematic trading, HFT, or quant development

Proven live trading experience

Strong understanding of PnL attribution and drawdowns

Crypto markets experience preferred (CeFi or DeFi)