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

Salary details

The average mid-level / intermediate Quantitative Researcher salary lies between USD 106,260 and USD 200,000 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 Researcher roles

The three most common job tag items assiciated with mid-level / intermediate Quantitative Researcher 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 | 58 jobs Research | 51 jobs Statistics | 51 jobs Machine Learning | 39 jobs Mathematics | 35 jobs PhD | 26 jobs Engineering | 25 jobs Physics | 24 jobs Trading Strategies | 23 jobs Finance | 23 jobs R | 21 jobs Computer Science | 21 jobs SQL | 13 jobs Matlab | 12 jobs Economics | 12 jobs Testing | 12 jobs Data analysis | 12 jobs NLP | 8 jobs Deep Learning | 7 jobs GPU | 6 jobs

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

The three most common job benefits and perks assiciated with mid-level / intermediate Quantitative Researcher 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 | 22 jobs Health care | 13 jobs Competitive pay | 13 jobs Salary bonus | 10 jobs Fitness / gym | 9 jobs Equity / stock options | 8 jobs 401(k) matching | 7 jobs Parental leave | 7 jobs Medical leave | 7 jobs Flex hours | 6 jobs Team events | 6 jobs Startup environment | 4 jobs Home office stipend | 4 jobs Fertility benefits | 4 jobs Flex vacation | 3 jobs Wellness | 3 jobs Snacks / Drinks | 2 jobs Lunch / meals | 1 jobs Conferences | 1 jobs Relocation support | 1 jobs

Salary Composition

In the United States, the salary composition for a Mid-level/Intermediate Quantitative Researcher 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 equity, especially in tech companies. The base salary often constitutes the majority of the total compensation package, ranging from 70% to 85%. Bonuses can vary significantly depending on the company's performance and individual contributions, usually making up 10% to 20% of the total compensation. Additional remuneration, such as stock options, is more common in larger tech firms or startups and can account for 5% to 15% of the total package. Regional differences also play a role; for instance, salaries in tech hubs like San Francisco or New York City tend to be higher due to the cost of living and competitive job markets. Industry-wise, finance and tech sectors often offer higher compensation compared to academia or government roles.

Increasing Salary

To increase your salary from a mid-level position, consider the following strategies:

• Skill Enhancement: Continuously update your skills in emerging AI/ML technologies and tools. Specializing in high-demand 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. or specialized certifications, can position you for senior roles with higher pay.

• Networking and Industry Engagement: Attend conferences, workshops, and seminars to build a strong professional network. Engaging with industry leaders can open up opportunities for higher-paying roles.

• Leadership and Management Skills: Developing skills in project management and leadership can prepare you for roles like team lead or manager, which typically come with higher salaries.

• Company Switch: Sometimes, moving to a different company, especially one in a high-paying industry or region, can result in a significant salary increase.

Educational Requirements

Most mid-level quantitative researcher positions in AI/ML/Data Science require at least a master's degree in a relevant field such as computer science, statistics, mathematics, or engineering. A strong foundation in quantitative analysis and programming is essential. Some positions may prefer candidates with a Ph.D., especially for roles that involve complex research and development tasks.

Helpful Certifications

While not always mandatory, certain certifications can enhance your profile and demonstrate expertise:

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

These certifications can validate your skills in specific tools and platforms, making you more attractive to potential employers.

Required Experience

Typically, a mid-level quantitative researcher role requires 3 to 5 years of relevant experience. This experience should include hands-on work with data analysis, machine learning model development, and statistical research. 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 research roles.

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