Sample cover letter for Internship position at AC

• Required: Candidate must possess at least an undergraduate degree in: finance, engineering, mathematics, statistics, computer science, actuarial science, economics or related technical field. Preferred: Graduate degree in: financial engineering, computational or mathematical finance, computer science, statistics or related field. Strong background in machine learning, hypothesis testing, regression analysis, statistics, or probability at the graduate school level or higher, as well as experience creating predictive analytics on noisy data. Background in text analytics, news aggregation and natural language processing.
• At least 3 years of experience and knowledge in the field of quantitative research and the specialized area of financial engineering, data science, or risk analytics as it relates to the securities industry. Knowledge of predictive model development and oversight.
• Knowledge of financial engineering to develop, maintain and/or validate models used for forecasting, valuation, instrument and strategy selection, portfolio construction, and risk management covering a wide range of financial instruments, including equities, fixed income, currencies, futures, commodities, and/or derivatives.
• Strong knowledge of advanced statistical methods, Bayesian learning techniques, pattern recognition and outlier detection algorithms, and predictive modeling methods including decision trees and random forest approaches.
• Experience in utilizing sophisticated models and products for managing risks in portfolio construction, trade decision, and execution and hedging, including multi-factor models such as BARRA; risk management metrics and methods such as VaR and stress testing models, valuation and pricing, and model sensitivity and risk statistics.
• Must be comfortable working and communicating both orally and in writing with a variety of people with varying skill and knowledge levels.
• Must be a self-starter and be able to handle multiple tasks independently and under tight deadlines.