Quantitative Researcher for a Systematic Investment firm

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