Quantitative Researcher for a Systematic Investment firm

Quanta Search • New York, NY

16d

About The Position

Our client is one of the world’s premier investment firms. The firm deploys systematic, computer-driven trading strategies across multiple liquid asset classes, including equities, futures, and foreign exchange. The core of this effort is rigorous research into a wide range of market anomalies, fueled by our unparalleled access to a wide range of publicly available data sources. Role/Responsibilities: Research and develop automated, rigorous, and innovative anomaly detection methods Develop models to explain unusual patterns or events Apply new models to data processing and trading activity monitoring infrastructure Conduct signal generation research Collaborate with colleagues to transform intuitions into rigorous research methodology Requirements: MS or PhD in statistics, engineering, applied math, computer science or other quantitative field with a strong foundation in statistics 2+ years of work experience at a financial services firm Demonstrated proficiency in Python, SQL R, or C/C++ Familiarly with data science toolkits, such as scikit-learn, Pandas, keras, and tensorflow Strong command of foundations of applied and theoretical statistics, linear algebra and vector manipulation, and machine learning techniques Understanding of the nuances and pitfalls of common models and modeling approaches, such as analyzing time-series based data vs. other types Ability to quickly and efficiently scrub, format, and manipulate large, raw data sources Strong knowledge of financial markets, instruments, and modeling/valuation is a plus Interest in experimenting with new types of data visualization is a plus Thank you for illuminating hiring with Quanta Search! www.quantasearch.com

Requirements

• MS or PhD in statistics, engineering, applied math, computer science or other quantitative field with a strong foundation in statistics
• 2+ years of work experience at a financial services firm
• Demonstrated proficiency in Python, SQL R, or C/C++
• Familiarly with data science toolkits, such as scikit-learn, Pandas, keras, and tensorflow
• Strong command of foundations of applied and theoretical statistics, linear algebra and vector manipulation, and machine learning techniques
• Understanding of the nuances and pitfalls of common models and modeling approaches, such as analyzing time-series based data vs. other types
• Ability to quickly and efficiently scrub, format, and manipulate large, raw data sources

Nice To Haves

• Strong knowledge of financial markets, instruments, and modeling/valuation is a plus
• Interest in experimenting with new types of data visualization is a plus

Responsibilities

• Research and develop automated, rigorous, and innovative anomaly detection methods
• Develop models to explain unusual patterns or events
• Apply new models to data processing and trading activity monitoring infrastructure
• Conduct signal generation research
• Collaborate with colleagues to transform intuitions into rigorous research methodology

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level