Salary for Mid-level / Intermediate Quantitative Analyst during 2024
💰 The median Salary for Mid-level / Intermediate Quantitative Analyst during 2024 is USD 117,900
✏️ This salary info is based on 9 individual salaries reported during 2024
Salary details
The average mid-level / intermediate Quantitative Analyst salary lies between USD 100,000 and USD 150,000 globally. 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.
- Job title
- Quantitative Analyst
- Experience
- Mid-level / Intermediate
- Region
- global/worldwide
- Salary year
- 2024
- Sample size
- 9
- Top 10%
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- Top 25%
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- Median
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- Bottom 25%
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- Bottom 10%
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All data shown are full-time equivalent (FTE) salaries. Part-time salary information has been extrapolated to its FTE value.
Last updated: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 jobsTop 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 jobsSalary Composition
The salary for a Mid-level/Intermediate Quantitative Analyst in AI/ML/Data Science typically comprises 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, usually around 70-80%. Bonuses can vary significantly depending on the company's performance and individual achievements, ranging from 10-20% of the base salary. Additional remuneration, such as stock options or profit-sharing, can make up the remaining 5-10%, though this varies widely based on the company's size and industry. In tech hubs like Silicon Valley, New York, or London, the total compensation might be higher due to the competitive market and cost of living.
Increasing Salary
To increase your salary from this position, consider pursuing advanced certifications or degrees, such as a Master's or Ph.D. in a related field. Gaining expertise in high-demand areas like deep learning, natural language processing, or big data analytics can also make you more valuable. Networking within industry-specific groups and attending conferences can open up opportunities for higher-paying roles. Additionally, taking on leadership roles or projects that demonstrate your ability to drive business value can position you for promotions or salary negotiations.
Educational Requirements
Most Mid-level/Intermediate Quantitative Analyst roles require at least a Bachelor's degree in a quantitative field such as Mathematics, Statistics, Computer Science, or Engineering. A Master's degree is often preferred and can be a significant advantage, especially in competitive markets. Some positions may also require coursework or experience in machine learning, data mining, or statistical modeling.
Helpful Certifications
Certifications can enhance your credentials and demonstrate your commitment to the field. Some valuable certifications include:
- Certified Analytics Professional (CAP)
- Microsoft Certified: Azure AI Engineer Associate
- Google Professional Machine Learning Engineer
- TensorFlow Developer Certificate
- Data Science Council of America (DASCA) Senior Data Scientist
These certifications can help validate your skills and knowledge, making you a more attractive candidate for higher-level positions.
Required Experience
Typically, a Mid-level/Intermediate Quantitative Analyst is expected to have 3-5 years of relevant experience. This experience should include hands-on work with data analysis, statistical modeling, and machine learning techniques. Experience in programming languages such as Python, R, or SQL is often required, along with familiarity with data visualization tools and platforms like Tableau or Power BI.
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