Applied Scientist Salary in United States during 2023

Salary details

The average Applied Scientist salary lies between USD 136,000 and USD 222,200 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

Salary trend

Top 20 Job Tags for Applied Scientist roles

The three most common job tag items assiciated with Applied Scientist job listings are Machine Learning, Research and Python. Below you find a list of the 20 most occuring job tags in 2023 and the number of open jobs that where associated with them during that period:

Machine Learning | 235 jobs Research | 189 jobs Python | 182 jobs Engineering | 157 jobs PhD | 140 jobs Deep Learning | 132 jobs Java | 127 jobs ML models | 120 jobs Statistics | 116 jobs Computer Science | 110 jobs TensorFlow | 85 jobs NLP | 76 jobs Computer Vision | 75 jobs PyTorch | 60 jobs Mathematics | 60 jobs Spark | 59 jobs AWS | 57 jobs R | 54 jobs Reinforcement Learning | 54 jobs Data Mining | 45 jobs

Top 20 Job Perks/Benefits for Applied Scientist roles

The three most common job benefits and perks assiciated with Applied Scientist job listings are Career development, Equity / stock options and Conferences. Below you find a list of the 20 most occuring job perks or benefits in 2023 and the number of open jobs that where offering them during that period:

Career development | 201 jobs Equity / stock options | 161 jobs Conferences | 96 jobs Startup environment | 82 jobs Health care | 64 jobs Competitive pay | 64 jobs Flex hours | 55 jobs Salary bonus | 54 jobs Flex vacation | 29 jobs Team events | 28 jobs Parental leave | 21 jobs Medical leave | 20 jobs Insurance | 17 jobs 401(k) matching | 14 jobs Transparency | 12 jobs Home office stipend | 10 jobs Wellness | 9 jobs Relocation support | 8 jobs Unlimited paid time off | 8 jobs Gear | 6 jobs

Salary Composition for an Applied Scientist in AI/ML/Data Science

The salary for an Applied Scientist in AI/ML/Data Science typically comprises a base salary, performance bonuses, and additional remuneration such as stock options or equity, especially in tech companies. The base salary is the fixed component and usually forms the largest part of the total compensation package. Performance bonuses can vary significantly depending on the company's performance and individual contributions, often ranging from 10% to 20% of the base salary. Additional remuneration, such as stock options, is more common in larger tech companies and startups, providing long-term incentives aligned with company growth.

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 market. Industry-wise, tech companies, financial services, and healthcare often offer higher compensation packages compared to academia or government roles. Company size can also influence salary composition, with larger companies typically offering more comprehensive benefits and stock options.

Steps to Increase Salary from an Applied Scientist Position

To increase your salary from an Applied Scientist position, consider the following strategies:

• Skill Enhancement: Continuously update and expand your skill set, particularly in emerging technologies and tools relevant to AI/ML. Specializing in niche areas can make you more valuable.
• Advanced Education: Pursuing further education, such as a Ph.D. or specialized certifications, can position you for higher-level roles.
• Leadership Roles: Transitioning into leadership or managerial roles can significantly increase your earning potential.
• Networking: Building a strong professional network can open up opportunities for higher-paying positions.
• Negotiation: Develop strong negotiation skills to better advocate for salary increases during performance reviews or when switching jobs.

Educational Requirements for an Applied Scientist

Most Applied Scientist roles in AI/ML/Data Science require at least a Master's degree in a relevant field such as Computer Science, Data Science, Statistics, or Electrical Engineering. A Ph.D. is often preferred, especially for research-intensive positions or roles in academia. The educational background should include a strong foundation in mathematics, statistics, and programming.

Helpful Certifications for an Applied Scientist

While not always mandatory, certain certifications can enhance your profile and demonstrate expertise. Some valuable certifications include:

• Certified Machine Learning Professional (CMLP)
• 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.

Experience Required for an Applied Scientist Role

Typically, an Applied Scientist role requires several years of experience in data science, machine learning, or a related field. This experience should include hands-on work with data analysis, model development, and deployment. Experience in a specific industry can also be beneficial, as it provides domain knowledge that can be crucial for certain roles.

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