Quant Trader

Role Summary
The ideal candidate will design and execute profitable trading strategies, leveraging statistical
and quantitative methods. You will closely with related team and management to refine
trading systems and maximize performance across diverse markets.

Key Responsibilities
Design Profitable Low/High-Frequency Options Market-Making Strategies.
Develop advanced algorithms to efficiently quote and trade options in high-frequency
environments.
Analyze large datasets to identify profitable trading opportunities.
Optimize strategies for consistent profitability.
Actively monitor and execute trading strategies across multiple markets and asset classes.
Manage and mitigate risks associated with trading activities.
Strategy Development and Optimization.
Collaborate with team to create, test, and deploy trading strategies.
Evaluate the performance of strategies and provide actionable insights.
Analyze market patterns and identify potential trading opportunities.
Conduct research on new trading opportunities using statistical and machine learning
techniques.
Stay updated on market trends, trading technologies, and regulatory changes.

Qualifications & Experience
Bachelor's or Master's degree in Finance, Mathematics, Economics, Computer Science,
or a related field.
Minimum 3 year in quantitative research, statistical analysis, or related fields.

Preferred Skills
Experience in high-frequency trading, options market-making, and managing PnL effectively.
Experience with time-series analysis and predictive modeling.
Familiarity with low-latency trading infrastructure.
Strong understanding of financial instruments and derivatives.
Knowledge of risk management and portfolio optimization techniques.
Proven ability to develop and implement advanced trading algorithms.
Proficiency in Python and R for statistical and data analysis.
Familiarity with C++ for performance optimization (preferred).
Knowledge of Linux/Unix operating systems.
Ability to analyze large datasets to uncover trading opportunities and market
inefficiencies.
Strong quantitative aptitude and analytical skills.
Strong interpersonal and collaboration skills to work within a multidisciplinary team.
Effective communication and decision-making abilities under pressure.
Experience applying machine learning techniques in financial markets.

What We Offer
A competitive compensation structure based on performance.
Access to cutting-edge technology and infrastructure.
A collaborative environment with experienced professionals.
Opportunities for growth and continuous learning.

Application Process
Interested candidates are encouraged to submit their resume and a cover letter to
[email removed].