Salary for Senior-level / Expert Research Scientist in United States during 2024

Salary details

The average senior-level / expert Research Scientist salary lies between USD 161,000 and USD 250,800 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: Nov. 17, 2024

Salary trend

Top 20 Job Tags for Senior-level / Expert Research Scientist roles

The three most common job tag items assiciated with senior-level / expert Research Scientist job listings are Research, Machine Learning and Python. 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:

Research | 750 jobs Machine Learning | 621 jobs Python | 539 jobs Computer Science | 478 jobs Engineering | 444 jobs PhD | 441 jobs Deep Learning | 333 jobs NLP | 288 jobs PyTorch | 280 jobs LLMs | 275 jobs Architecture | 240 jobs Statistics | 225 jobs Mathematics | 219 jobs Computer Vision | 193 jobs TensorFlow | 183 jobs Generative AI | 179 jobs Physics | 172 jobs NeurIPS | 161 jobs ML models | 151 jobs ICML | 142 jobs

Top 20 Job Perks/Benefits for Senior-level / Expert Research Scientist roles

The three most common job benefits and perks assiciated with senior-level / expert Research Scientist job listings are Career development, Equity / stock options and Health care. 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 | 591 jobs Equity / stock options | 394 jobs Health care | 368 jobs Conferences | 304 jobs Salary bonus | 218 jobs Flex hours | 193 jobs Flex vacation | 163 jobs Competitive pay | 159 jobs Medical leave | 136 jobs Parental leave | 132 jobs Insurance | 129 jobs 401(k) matching | 124 jobs Startup environment | 99 jobs Wellness | 91 jobs Team events | 85 jobs Relocation support | 46 jobs Flexible spending account | 46 jobs Unlimited paid time off | 32 jobs Transparency | 22 jobs Fitness / gym | 18 jobs

Salary Composition

In the United States, the salary composition for a Senior-level or Expert Research Scientist 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 largest portion, ranging from 60% to 80% of the total compensation package. Bonuses can vary significantly depending on the company's performance and individual contributions, usually accounting for 10% to 20% of the total salary. Additional remuneration, such as stock options, can be a significant part of the package, particularly in startups or large tech firms, and may range from 10% to 30% of the total compensation. The exact composition can vary based on the region, with tech hubs like Silicon Valley offering higher equity components, and the industry, with finance and healthcare often providing higher base salaries. Company size also plays a role, with larger companies typically offering more structured bonus and equity packages.

Increasing Salary Further

To increase your salary beyond the median of USD 200,200, consider the following strategies:

• Specialization: Develop expertise in a niche area of AI/ML that is in high demand, such as deep learning, natural language processing, or AI ethics.
• Leadership Roles: Transition into leadership or managerial roles, such as leading a research team or becoming a director of AI/ML research.
• Continuous Learning: Stay updated with the latest advancements in AI/ML through courses, workshops, and conferences. This not only enhances your skills but also increases your value to employers.
• Networking: Build a strong professional network in the AI/ML community. This can lead to opportunities in higher-paying roles or consulting gigs.
• Publications and Patents: Contribute to the field through research publications or patents, which can enhance your reputation and bargaining power for salary negotiations.

Educational Requirements

For a Senior-level or Expert Research Scientist position in AI/ML/Data Science, a Ph.D. in a related field such as Computer Science, Data Science, Statistics, or Electrical Engineering is often preferred. However, a Master's degree with significant experience and a strong portfolio of projects can also be sufficient. The educational background should include a solid foundation in mathematics, statistics, and computer programming, with coursework or research experience in machine learning, data mining, and artificial intelligence.

Helpful Certificates

While not always required, certain certifications can enhance your credentials and demonstrate your commitment to the field. Some valuable certifications include:

• Certified Machine Learning Professional (CMLP)
• TensorFlow Developer Certificate
• AWS Certified Machine Learning – Specialty
• Microsoft Certified: Azure AI Engineer Associate
• Data Science Professional Certificate by IBM

These certifications can provide a competitive edge, especially if they align with the technologies and tools used by your target employers.

Required Experience

Typically, a Senior-level or Expert Research Scientist role requires at least 5 to 10 years of experience in AI/ML or data science. This experience should include hands-on work with machine learning models, data analysis, and algorithm development. Experience in leading projects, mentoring junior team members, and contributing to strategic decision-making is also highly valued. A proven track record of successful projects, publications, or patents can significantly bolster your application.

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