Salary for Mid-level / Intermediate Quantitative Researcher during 2024

Salary details

The average mid-level / intermediate Quantitative Researcher salary lies between USD 112,500 and USD 205,000 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.

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

The salary for a Mid-level/Intermediate Quantitative Researcher 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 often the largest component, accounting for 70-80% of the total compensation package. Performance bonuses can vary significantly depending on the company and industry, ranging from 10-20% of the total salary. In tech hubs like Silicon Valley or New York, additional remuneration such as stock options or equity can be a significant part of the package, especially in startups or large tech companies. In contrast, in regions with a lower cost of living or in smaller companies, the base salary might be more dominant, with fewer additional incentives.

Increasing Salary

To increase your salary from this position, consider pursuing advanced roles such as Senior Quantitative Researcher or Lead Data Scientist. This often requires demonstrating leadership skills, taking on more complex projects, and contributing to strategic decision-making. Networking within the industry and building a strong professional reputation can also open doors to higher-paying opportunities. Additionally, specializing in high-demand areas like deep learning, natural language processing, or financial modeling can make you more valuable to employers. Pursuing further education, such as a Ph.D. or an MBA with a focus on data science, can also enhance your qualifications and salary prospects.

Educational Requirements

Most mid-level quantitative researcher roles 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 require a Ph.D., especially in research-intensive roles or in academia. Employers often look for candidates with a solid understanding of machine learning algorithms, statistical modeling, and data analysis techniques.

Helpful Certificates

While not always mandatory, certain certifications can enhance your profile and demonstrate your expertise. Certifications such as the Certified Analytics Professional (CAP), TensorFlow Developer Certificate, or AWS Certified Machine Learning can be beneficial. These certifications validate your skills in specific tools and platforms commonly used in the industry. Additionally, completing online courses from platforms like Coursera, edX, or Udacity in specialized areas of AI/ML can also be advantageous.

Required Experience

Typically, a mid-level quantitative researcher is expected to have 3-5 years of relevant experience. This experience should include hands-on work with data analysis, machine learning model development, and quantitative research projects. Experience in a specific industry, such as finance, healthcare, or technology, can be particularly valuable, as it provides domain-specific insights that are often crucial for effective research and analysis.

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