HFT Quant Trader

About Us
Quanta Trading is a dynamic high-frequency trading firm operating across both cryptocurrency markets and traditional financial markets, with a focus on trading highly liquid asset classes. Our mission is to develop and deploy state-of-the-art quantitative trading strategies supported by low-latency technology, robust research, and disciplined risk management.

Founded by a team of industry veterans with extensive experience in high-frequency trading, Quanta Trading combines deep market expertise, quantitative research, cutting-edge technology, and robust infrastructure to stay at the forefront of modern trading. We embrace a flexible work environment and support remote working, enabling our team to collaborate and innovate from anywhere in the world.

Responsibilities

• Research, develop, backtest, deploy, and continuously improve systematic quantitative trading strategies across cryptocurrency and/or traditional financial markets.
• Develop strategies across high-frequency and mid-frequency trading horizons, with particular interest in:
• Market Making
• Cross-Exchange Arbitrage
• Spot-Perpetual / Spot-Futures Arbitrage
• Basis and Funding Rate Arbitrage
• RWA / Tokenized Asset Market Making
• Statistical Arbitrage
• Relative-Value Trading
• Short-Term Alpha / Predictive Strategies
• Other scalable HFT and systematic trading strategies
• Identify market inefficiencies and transform trading ideas into systematic, testable, and production-ready strategies.
• Conduct rigorous quantitative research using historical and real-time market data, including order book, trade, funding, position, and other relevant datasets.
• Build robust backtesting and simulation frameworks that appropriately model transaction costs, exchange fees, market impact, latency, slippage, funding costs, and execution constraints.
• Work closely with developers and infrastructure engineers to translate research strategies into production trading systems.
• Optimize execution logic, order placement, inventory management, position sizing, and risk controls to improve strategy performance.
• Analyze trading performance at both strategy and portfolio levels, including P&L attribution, Sharpe ratio, return on capital, drawdown, turnover, adverse selection, execution quality, and capacity.
• Monitor live strategies and identify opportunities to improve profitability, robustness, capital efficiency, and scalability.
• Develop appropriate risk management frameworks, including position limits, inventory limits, stop-loss mechanisms, exposure controls, and exchange/counterparty risk controls.
• For market-making strategies, research and optimize areas including quoting models, spread determination, inventory skew, adverse-selection management, fill probability, order-book dynamics, and short-term price prediction.
• For arbitrage strategies, identify and exploit pricing discrepancies across exchanges, instruments, venues, and related assets while considering execution risk, latency, capital allocation, and transaction costs.
• For crypto strategies, research opportunities across both CEX and DEX markets, including differences in market structure, liquidity, execution, settlement, and on-chain dynamics.
• Stay up-to-date with developments in quantitative trading, market microstructure, exchange mechanisms, DeFi, tokenized assets, and emerging trading venues.

Qualifications

• Bachelor's degree or higher in a quantitative field such as Mathematics, Statistics, Physics, Computer Science, Engineering, Financial Engineering, Economics, or a related discipline.
• 5+ years of professional quantitative trading or quantitative research experience, preferably with a proprietary trading firm, hedge fund, market maker, investment bank, or other systematic trading organization.
• Proven experience developing and/or managing profitable systematic trading strategies in live markets.
• Strong experience in at least one or more of the following areas:
• High-Frequency Market Making
• Cross-Exchange Arbitrage
• Spot-Perpetual / Futures Arbitrage
• Statistical Arbitrage
• Relative-Value Trading
• Short-Term Alpha Strategies
• RWA / Tokenized Asset Market Making
• Other HFT or Mid-Frequency Systematic Strategies
• Strong understanding of market microstructure, including order books, matching engines, maker/taker dynamics, liquidity, spreads, queue position, adverse selection, and execution costs.
• Strong quantitative and statistical research skills, with the ability to distinguish genuine trading signals from overfitting and statistical noise.
• Strong understanding of strategy performance measurement and risk management, including Sharpe ratio, drawdown, volatility, turnover, capacity, leverage, and return on capital.
• Proficiency in Python for quantitative research, data analysis, backtesting, and strategy prototyping.
• Familiarity with C++ and low-latency trading systems is highly desirable, although the ability to conduct high-quality quantitative research and develop profitable strategies is the primary requirement.
• Excellent problem-solving skills and the ability to work independently as well as collaboratively with traders, researchers, and developers.
• Ability to work in a fast-paced and highly performance-driven environment.
• Comfortable working in across-cultural, global environment with high expectations.
• High attention to detail analytical, thorough, organized, and self-motivated.

Preferred Skills

• Track record of developing strategies with demonstrated live trading P&L, rather than research or backtesting experience alone.
• Experience trading cryptocurrency markets across major CEXs such as Binance, Bybit, OKX, Coinbase, Kraken, or other major venues.
• Experience with decentralized exchanges (DEXs), AMMs, on-chain liquidity, DeFi protocols, or blockchain market structure.
• Experience in traditional asset classes such as equities, futures, options, FX, commodities, or fixed income is also highly relevant.
• Experience with RWA and tokenized financial markets, particularly market making, liquidity provision, or arbitrage between tokenized and traditional instruments.
• Deep knowledge of order-book dynamics, execution algorithms, smart order routing, and latency-sensitive trading.
• Experience working with tick/order-book data and large-scale high-frequency datasets.
• Familiarity with exchange APIs, WebSocket market data, FIX protocols, and electronic trading infrastructure.
• Experience with portfolio construction and capital allocation across multiple systematic strategies.
• Ability to independently take a trading idea through the complete lifecycle: Idea → Research → Backtest →Simulation → Production → Live Trading → Performance Analysis → Optimization.

What We Are Looking For

We are particularly interested in experienced quantitative traders who can bring both research capability and practical live-trading experience.

The ideal candidate should be able to independently identify trading opportunities, conduct rigorous quantitative research, work with our engineering team to deploy strategies into production, and take ownership of their strategies live performance.

We welcome candidates from both traditional proprietary trading / hedge fund backgrounds and digital-asset trading firms. Prior crypto experience is preferred but not mandatory if the candidate has a strong track record in transferable HFT, market-making, arbitrage, or systematic trading strategies.