Quantitative analysts often referred as ‘quants’, are professionals who specialises in the design, development, and implementation of algorithms and mathematical or statistical models used for solving complex financial problems. Quantitative analysts usually apply mix of techniques and knowledge obtained from multiple disciplines like finance, economics, mathematics, statistics, and computer science. In this article let see what are the roles, responsibilities and educational qualifications required to become a successful quantitative analysts.
Quantitative Analyst responsibilities:
Responsibilities may differ according to employers, product focus and level of expertise. Following are the responsibilities a quant possibly require to –
1. Maintain and modify analytical models
2. Perform daily statistical analysis and coding task
3. Test new models, products and analytics programs
4. Apply or originate independent tools to verify results
5. Collaborate with teams of mathematicians, computer engineers, and physicists to develop optimal strategies.
6. Generate requirement documentation for software developers
7. Interpret and present data results to senior management and clients
Skills and Traits Need to Become a Quantitative Analyst
To become a quantitative analyst, one needs to possess a certain set of skills and personality traits. Quantitative analyst must have excellent written and verbal communication skills and outstanding abilities in mathematics, statistics, and data mining and data-intensive analysis. They must also possess’ strong computer programming skills, including object-oriented programming and familiarity with programming languages such as C++. A strong understanding of systematic and discretionary trading practices, financial modeling and interest rate derivatives is also necessary for quantitative analysts.
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In order to get a job as a Quantitative Analyst, most firms typically require a master degree in quantitative finance, financial engineering or a related quantitative field such as physics, Math’s or statistics. Some employers may require a Ph.D. for a senior-level position. Master’s degrees in Financial Engineering or Computational Finance are also useful if you want to become a quantitative analyst. Quants should also acquire experience in coding and knowledge of programming languages such as C++, Java, R, Python, and MATLAB.
Career Paths and Job Prospects for Quantitative Analyst
Quantitative analysts as a career are both lucrative and intellectually stimulating. As analyst is highly competitive in this field, aspirants need to have a refined skill set in the areas of managing risk, financial research, systematic trading, options pricing, or quantitative programming. Some of the possible paths which Quantitative analysts may choose or want to specialize are Risk management, Algorithmic trading, Library Quantitative Analysis, and Front office quant. The quantitative analyst is employed by hedge funds, investment banks, Commercial banks, Insurance companies, management consulting firms, brokerage firms, securities and commodities traders, and accounting companies.
Some quantitative financial analysts start working in entry-level roles as research analysts after completing a bachelor’s degree with practical quantitative skills like finance, statistics, or economics. Though, these positions do not typically lead to long-term, permanent careers in the field. Quantitative analysts are hired for their expertise in complex mathematical modeling techniques and skills in the securities industry, that require many years of training to develop. Consequently, a majority of quantitative analysts come to the field after completing a master’s degree or doctorate.
The quantitative analyst job is comparatively new because quantitative analysis only started to rapidly grow in the second half of the 20th century when more sophisticated quantitative methods were initiated in finance. The mass computerization of finance operations and the introduction of compound securities further fueled the requirement for quantitative analysts. The recent popularity of data science and machine learning generate new opportunities for people interested in the job of a quantitative analyst.
Courtesy: HIGHER EDUCATION Review
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