Quantitative Researcher

Joseph Anthony Group; New York (NY); On-site; USD 140,000 - 200,000; Full time

Job summary

Joseph Anthony Group in New York seeks a technically strong Quantitative Researcher to join its NY-based trading team. You will research digital asset markets, develop systematic trading strategies, and leverage real-time data to identify alpha opportunities.

The role requires advanced statistics, ML techniques, and proficiency in C++/Python, with experience in high-frequency or electronic trading. You will build research infrastructure, backtest frameworks, and collaborate with engineering to

Qualifications

• Master's or PhD in Mathematics, Statistics, Physics, Computer Science, Financial Engineering, or a related quantitative field.
• 3+ years of experience in quantitative research, systematic trading, quantitative development, or a related discipline, ideally within a high-frequency or electronic trading environment.

Responsibilities

• Analyze market microstructure, trading data, and blockchain datasets to identify alpha opportunities.
• Develop and refine quantitative signals using statistical and machine learning techniques.
• Design, test, and deploy systematic trading strategies, including market-making and arbitrage models.
• Build and maintain research infrastructure, data pipelines, and backtesting frameworks.
• Conduct performance analysis, attribution, and post-trade execution reviews.
• Develop risk monitoring tools and controls across trading strategies and venues.
• Collaborate with engineering and trading teams to optimize production systems, execution quality, and scalability.

Skills

Probability & statistics

Time-series analysis

C++/Python

Education

Master's or PhD in quantitative field

Job description

Our client is a leading Web3 and blockchain technology company building next-generation infrastructure for digital assets and decentralized finance. The company develops scalable blockchain solutions, advanced trading technology, and financial applications that support a rapidly evolving digital asset ecosystem. With a team comprised of experienced professionals from top financial institutions, quantitative trading firms, and technology companies, the organization is focused on driving innovation at the intersection of blockchain technology and global financial markets.

About the Role

Seeking a technical Quantitative Researcher to join its New York-based quantitative trading team. You will research digital asset markets, develop systematic trading strategies, and leverage real-time market data to identify and execute trading opportunities. This role is ideal for a technically strong quant who thrives in a fast-paced, research-driven environment and has an interest in crypto markets and blockchain technology.

Responsibilities

• Analyze market microstructure, trading data, and blockchain datasets to identify alpha opportunities.
• Develop and refine quantitative signals using statistical and machine learning techniques.
• Design, test, and deploy systematic trading strategies, including market-making and arbitrage models.
• Build and maintain research infrastructure, data pipelines, and backtesting frameworks.
• Conduct performance analysis, attribution, and post-trade execution reviews.
• Develop risk monitoring tools and controls across trading strategies and venues.
• Collaborate with engineering and trading teams to optimize production systems, execution quality, and scalability.

Qualifications

• Master's or PhD in Mathematics, Statistics, Physics, Computer Science, Financial Engineering, or a related quantitative field.
• 3+ years of experience in quantitative research, systematic trading, quantitative development, or a related discipline, ideally within a high-frequency or electronic trading environment.

Required Skills

• Strong foundation in probability, statistics, quantitative modeling, and time-series analysis.
• Advanced C++/Python programming skills and experience working with large datasets and research frameworks.
• Solid understanding of financial markets, algorithmic trading, market microstructure, and risk management principles.