Salary for Senior-level / Expert Applied Scientist in United States during 2022

Salary details

The average senior-level / expert Applied Scientist salary lies between USD 184,000 and USD 205,000 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: Nov. 17, 2024

Salary trend

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

The three most common job tag items assiciated with senior-level / expert Applied Scientist job listings are Machine Learning, Python and Research. Below you find a list of the 20 most occuring job tags in 2022 and the number of open jobs that where associated with them during that period:

Machine Learning | 143 jobs Python | 126 jobs Research | 120 jobs PhD | 112 jobs Engineering | 107 jobs Computer Science | 99 jobs ML models | 90 jobs Deep Learning | 87 jobs Statistics | 85 jobs Mathematics | 67 jobs NLP | 59 jobs Computer Vision | 50 jobs AWS | 46 jobs PyTorch | 41 jobs TensorFlow | 36 jobs Spark | 28 jobs Economics | 27 jobs Data analysis | 27 jobs Big Data | 26 jobs R | 23 jobs

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

The three most common job benefits and perks assiciated with senior-level / expert Applied Scientist job listings are Career development, Conferences and Startup environment. Below you find a list of the 20 most occuring job perks or benefits in 2022 and the number of open jobs that where offering them during that period:

Career development | 103 jobs Conferences | 74 jobs Startup environment | 31 jobs Flex hours | 30 jobs Health care | 26 jobs Equity / stock options | 24 jobs Competitive pay | 23 jobs Flex vacation | 20 jobs Team events | 20 jobs Parental leave | 18 jobs Salary bonus | 14 jobs Medical leave | 13 jobs Insurance | 12 jobs Wellness | 8 jobs Fitness / gym | 8 jobs Relocation support | 6 jobs Signing bonus | 4 jobs Snacks / Drinks | 4 jobs 401(k) matching | 3 jobs Lunch / meals | 3 jobs

Salary Composition

In the United States, the salary for a Senior-level or Expert Applied Scientist in AI/ML/Data Science typically comprises several components. The fixed base salary is the largest portion, often accounting for 70-80% of the total compensation package. Bonuses, which can be performance-based or tied to company profits, usually make up 10-20% of the total salary. Additional remuneration may include stock options, especially in tech companies, which can vary significantly depending on the company's size and success. Benefits such as health insurance, retirement plans, and other perks also contribute to the overall compensation package. The exact composition can vary by region, with tech hubs like Silicon Valley offering higher base salaries and stock options, while other regions might offer more competitive bonuses.

Increasing Salary

To increase your salary from a Senior-level position, 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 computer vision.
• Leadership Roles: Transition into leadership or managerial roles, such as a Director of Data Science or Chief Data Scientist, which typically offer higher salaries.
• Industry Shift: Move to industries that pay a premium for AI/ML expertise, such as finance, healthcare, or autonomous vehicles.
• Networking and Visibility: Increase your visibility in the field by speaking at conferences, publishing research, or contributing to open-source projects, which can lead to higher-paying opportunities.
• Negotiation: Leverage offers from other companies to negotiate a higher salary with your current employer.

Educational Requirements

Most Senior-level or Expert Applied Scientist roles require at least a Master's degree in a relevant field such as Computer Science, Data Science, Statistics, or Mathematics. A Ph.D. is often preferred, especially for roles that involve research and development of new algorithms or technologies. The educational background should include a strong foundation in machine learning, data analysis, and programming.

Helpful Certificates

While not always required, certain certifications can enhance your qualifications and demonstrate your expertise:

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

These certifications can help validate your skills and make you more competitive in the job market.

Required Experience

Typically, a Senior-level or Expert Applied Scientist position requires at least 5-10 years of experience in the field. This experience should include hands-on work with machine learning models, data analysis, and software development. Experience in leading projects, mentoring junior team members, and collaborating with cross-functional teams is also highly valued.

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