Salary for Mid-level / Intermediate Quantitative Analyst in United States during 2024

Salary details

The average mid-level / intermediate Quantitative Analyst salary lies between USD 82,200 and USD 150,000 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. 22, 2024

Top 20 Job Tags for Mid-level / Intermediate Quantitative Analyst roles

The three most common job tag items assiciated with mid-level / intermediate Quantitative Analyst job listings are Python, Research and Statistics. 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 | 25 jobs Research | 22 jobs Statistics | 21 jobs Finance | 17 jobs Economics | 16 jobs Mathematics | 16 jobs SQL | 14 jobs R | 13 jobs Engineering | 13 jobs Machine Learning | 11 jobs Physics | 11 jobs RDBMS | 10 jobs Spark | 8 jobs Data visualization | 8 jobs SAS | 8 jobs Tableau | 7 jobs Testing | 7 jobs Excel | 7 jobs Scala | 6 jobs Computer Science | 6 jobs

Top 20 Job Perks/Benefits for Mid-level / Intermediate Quantitative Analyst roles

The three most common job benefits and perks assiciated with mid-level / intermediate Quantitative Analyst job listings are Career development, Health care and Startup environment. 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 | 21 jobs Health care | 11 jobs Startup environment | 7 jobs Competitive pay | 7 jobs Equity / stock options | 4 jobs Flex vacation | 3 jobs Wellness | 3 jobs 401(k) matching | 2 jobs Flex hours | 2 jobs Conferences | 2 jobs Team events | 2 jobs Medical leave | 2 jobs Insurance | 2 jobs Salary bonus | 2 jobs

Salary Composition

In the United States, the salary composition for a Mid-level/Intermediate Quantitative Analyst in AI/ML/Data Science typically includes a combination of a fixed base salary, performance-based bonuses, and additional remuneration such as stock options or profit-sharing. The fixed base salary often constitutes the majority of the total compensation package, ranging from 60% to 80%. Bonuses can vary significantly depending on the company's performance and individual contributions, usually accounting for 10% to 20% of the total compensation. Additional remuneration, such as stock options or other incentives, can make up the remaining 5% to 15%.

The composition can vary based on several factors:

• Region: Salaries in tech hubs like San Francisco, New York, and Seattle tend to be higher due to the cost of living and demand for talent.
• Industry: Financial services and tech companies often offer higher bonuses and stock options compared to other industries.
• Company Size: Larger companies may offer more comprehensive benefits and stock options, while startups might provide higher equity stakes in lieu of a higher base salary.

Increasing Salary

To increase your salary from a Mid-level/Intermediate position, consider the following strategies:

• Skill Enhancement: Continuously update 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 a master's or Ph.D. in a relevant field can open up higher-paying opportunities.
• Leadership Roles: Transitioning into roles with leadership responsibilities, such as a team lead or project manager, can lead to salary increases.
• Networking: Building a strong professional network can lead to opportunities in higher-paying companies or industries.
• Certifications: Obtaining advanced certifications can demonstrate expertise and justify a higher salary.

Educational Requirements

Most Mid-level/Intermediate Quantitative Analyst positions require at least a bachelor's degree in a quantitative field such as Computer Science, Mathematics, Statistics, Engineering, or Physics. A master's degree is often preferred and can be a significant advantage, especially in competitive markets. Some roles may also require coursework or experience in machine learning, data analysis, and programming languages like Python or R.

Helpful Certifications

While not always mandatory, certain certifications can enhance your profile and demonstrate your commitment to the field:

• Certified Analytics Professional (CAP)
• Google Professional Machine Learning Engineer
• AWS Certified Machine Learning – Specialty
• Microsoft Certified: Azure AI Engineer Associate
• TensorFlow Developer Certificate

These certifications can validate your skills and knowledge, making you a more attractive candidate for higher-paying roles.

Experience Requirements

Typically, a Mid-level/Intermediate Quantitative Analyst role requires 3 to 5 years of relevant experience. This experience should include hands-on work with data analysis, statistical modeling, and machine learning projects. Experience in a specific industry, such as finance, healthcare, or technology, can also be beneficial, as it provides domain-specific insights that are valuable in data-driven decision-making.

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