Quantitative Analyst Salary in United States during 2024

Salary details

The average Quantitative Analyst salary lies between USD 88,200 and USD 165,100 in the United States. It represents the overall compensation/gross salary amount for the working year (before deductions like social security, taxes and other contributions), not including equity/stock options or similar benefits.

Region represents the primary country of residence of an employee during the year (or residence for tax purposes). All data shown are full-time equivalent (FTE) salaries. Part-time salary information has been extrapolated to its FTE value.

Last updated: Dec. 15, 2024

Top 20 Job Tags for Quantitative Analyst roles

The three most common job tag items assiciated with Quantitative Analyst job listings are Python, Statistics and Mathematics. Below you find a list of the 20 most occuring job tags in 2024 and the number of open jobs that where associated with them during that period:

Python | 172 jobs Statistics | 162 jobs Mathematics | 111 jobs Finance | 99 jobs Research | 95 jobs Engineering | 91 jobs R | 82 jobs SQL | 80 jobs Testing | 71 jobs Machine Learning | 70 jobs Economics | 63 jobs Physics | 57 jobs ML models | 54 jobs Computer Science | 54 jobs Data analysis | 49 jobs Credit risk | 42 jobs SAS | 42 jobs PhD | 41 jobs Trading Strategies | 34 jobs Banking | 34 jobs

Top 20 Job Perks/Benefits for Quantitative Analyst roles

The three most common job benefits and perks assiciated with Quantitative Analyst job listings are Career development, Health care and Competitive pay. Below you find a list of the 20 most occuring job perks or benefits in 2024 and the number of open jobs that where offering them during that period:

Career development | 119 jobs Health care | 74 jobs Competitive pay | 50 jobs Equity / stock options | 36 jobs Flex hours | 36 jobs Startup environment | 29 jobs Insurance | 26 jobs Team events | 24 jobs Flex vacation | 21 jobs Salary bonus | 17 jobs Medical leave | 16 jobs Wellness | 15 jobs Parental leave | 13 jobs 401(k) matching | 7 jobs Transparency | 4 jobs Conferences | 4 jobs Fitness / gym | 3 jobs Paid sabbatical | 2 jobs Lunch / meals | 1 jobs Travel | 1 jobs

Salary Composition for Quantitative Analysts in AI/ML/Data Science

The salary for a Quantitative Analyst in AI/ML/Data Science typically comprises a base salary, performance bonuses, and additional remuneration such as stock options or profit-sharing. The base salary is the fixed component and can vary significantly depending on the region, industry, and company size. For instance, tech hubs like San Francisco or New York often offer higher base salaries compared to other regions due to the higher cost of living and competitive job market. Performance bonuses are usually tied to individual or company performance and can range from 10% to 30% of the base salary. Additional remuneration might include stock options, especially in tech companies or startups, which can be a significant part of the total compensation package.

Steps to Increase Salary from This Position

To increase your salary from the position of a Quantitative Analyst, consider the following strategies:

• Skill Enhancement: Continuously upgrade your skills in emerging AI/ML technologies and tools. Specializing in niche areas like deep learning, natural language processing, or reinforcement learning can make you more valuable.
• Advanced Education: Pursuing further education, such as a Ph.D. in a relevant field, can open doors to higher-level positions and salary brackets.
• Networking: Build a strong professional network within the industry. Attend conferences, workshops, and seminars to connect with industry leaders and peers.
• Leadership Roles: Aim for leadership or managerial roles within your organization, which typically come with higher compensation.
• Switching Companies: Sometimes, moving to a different company can result in a significant salary increase, especially if you are moving to a larger firm or one in a more lucrative industry.

Educational Requirements

Most Quantitative Analyst positions in AI/ML/Data Science require at least a master's degree in a related field such as Computer Science, Mathematics, Statistics, or Engineering. A strong foundation in quantitative disciplines is essential. Some positions, especially those in research or academia, may require a Ph.D. Additionally, coursework or experience in machine learning, data analysis, and programming languages like Python or R is highly beneficial.

Helpful Certifications

While not always mandatory, certain certifications can enhance your profile and demonstrate your expertise to potential employers. Some valuable certifications include:

• Certified Data Scientist (CDS)
• TensorFlow Developer Certificate
• AWS Certified Machine Learning – Specialty
• Microsoft Certified: Azure AI Engineer Associate
• SAS Certified AI & Machine Learning Professional

These certifications can validate your skills and knowledge in specific tools and platforms used in the industry.

Experience Requirements

Typically, employers look for candidates with at least 2-5 years of experience in a related field. This experience should include hands-on work with data analysis, statistical modeling, and machine learning projects. Experience in financial modeling or risk management can be particularly advantageous for roles in finance-related industries.

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