Salary for Mid-level / Intermediate Applied Scientist in United States during 2023

Salary details

The average mid-level / intermediate 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 Mid-level / Intermediate Applied Scientist roles

The three most common job tag items assiciated with mid-level / intermediate Applied Scientist job listings are Machine Learning, Python and Research. 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 | 21 jobs Python | 20 jobs Research | 18 jobs Deep Learning | 13 jobs Generative AI | 13 jobs Computer Vision | 12 jobs TensorFlow | 11 jobs PyTorch | 11 jobs Statistics | 11 jobs Data Mining | 9 jobs Engineering | 9 jobs PhD | 9 jobs Java | 9 jobs ML models | 8 jobs NeurIPS | 8 jobs ICML | 8 jobs GANs | 8 jobs Linux | 5 jobs Computer Science | 5 jobs R | 4 jobs

Top 20 Job Perks/Benefits for Mid-level / Intermediate Applied Scientist roles

The three most common job benefits and perks assiciated with mid-level / intermediate Applied Scientist job listings are Career development, Equity / stock options and Startup environment. 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 | 18 jobs Equity / stock options | 16 jobs Startup environment | 13 jobs Health care | 12 jobs Competitive pay | 8 jobs Insurance | 8 jobs Conferences | 6 jobs Parental leave | 2 jobs Flex hours | 2 jobs Flex vacation | 2 jobs Team events | 2 jobs Relocation support | 2 jobs Medical leave | 2 jobs Paid sabbatical | 2 jobs Wellness | 1 jobs Fitness / gym | 1 jobs Pet friendly | 1 jobs Salary bonus | 1 jobs

Salary Composition

The salary for a Mid-level/Intermediate 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 profitability and individual performance metrics. Additional remuneration, like stock options, is more common in larger tech companies or startups, where equity is used as an incentive. The composition can also vary by region, with tech hubs like Silicon Valley offering higher base salaries and more substantial equity packages compared to other regions. Industry also plays a role; for instance, finance and healthcare sectors might offer higher bonuses compared to academia or non-profits.

Increasing Salary

To increase your salary from this position, consider pursuing advanced roles such as Senior Applied Scientist or transitioning into managerial positions like a Data Science Manager. Gaining expertise in high-demand areas such as deep learning, natural language processing, or AI ethics can also make you more valuable. Networking within industry circles and attending conferences can open up opportunities for higher-paying roles. Additionally, obtaining a Ph.D. or an MBA can provide leverage for salary negotiations. Exploring opportunities in different industries or regions where the demand for AI/ML expertise is higher can also lead to better compensation.

Educational Requirements

Most mid-level 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 models. The educational background should include a strong foundation in machine learning, data analysis, and programming languages like Python or R. Courses in data structures, algorithms, and software engineering are also beneficial.

Helpful Certificates

While not always mandatory, certain certifications can enhance your profile. Certifications in machine learning from platforms like Coursera, edX, or Udacity can be beneficial. The TensorFlow Developer Certificate or AWS Certified Machine Learning – Specialty are also recognized in the industry. These certifications demonstrate a commitment to continuous learning and proficiency in specific tools and technologies.

Experience Requirements

Typically, a mid-level applied scientist is expected to have 3-5 years of experience in data science or a related field. This experience should include hands-on work with machine learning models, data analysis, and software development. Experience in deploying models to production and working with large datasets is often required. Prior experience in a specific industry can be advantageous, as it provides domain knowledge that can be critical for certain roles.

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