Salary for Mid-level / Intermediate Applied Scientist in United States during 2024

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: Nov. 24, 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 PhD. 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:

Machine Learning | 163 jobs Python | 147 jobs PhD | 138 jobs Research | 129 jobs Java | 125 jobs Deep Learning | 93 jobs Data Mining | 87 jobs Engineering | 86 jobs LLMs | 76 jobs Computer Science | 75 jobs ML models | 67 jobs Linux | 66 jobs Statistics | 60 jobs NLP | 56 jobs Generative AI | 55 jobs PyTorch | 49 jobs TensorFlow | 43 jobs Security | 39 jobs Computer Vision | 37 jobs AWS | 37 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, Conferences and Equity / stock options. 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 | 151 jobs Conferences | 100 jobs Equity / stock options | 94 jobs Startup environment | 44 jobs Medical leave | 32 jobs Team events | 29 jobs Health care | 25 jobs Flex hours | 17 jobs Parental leave | 9 jobs Relocation support | 5 jobs Flex vacation | 4 jobs Competitive pay | 4 jobs Insurance | 4 jobs Home office stipend | 4 jobs 401(k) matching | 3 jobs Flexible spending account | 3 jobs Salary bonus | 2 jobs Wellness | 1 jobs Gear | 1 jobs Fitness / gym | 1 jobs

Salary Composition

In the United States, the salary composition for a Mid-level/Intermediate Applied Scientist in AI/ML/Data Science typically includes a combination of base salary, bonuses, and additional remuneration such as stock options or equity, especially in tech companies. The base salary is the fixed component and usually constitutes the majority of the total compensation package. Bonuses can vary significantly depending on the company's performance, individual performance, and industry standards. In tech hubs like Silicon Valley, Seattle, or New York, companies often offer substantial bonuses and stock options to attract top talent. In contrast, smaller companies or those in less competitive regions might offer a higher base salary with smaller bonuses or equity options. Industry also plays a role; for instance, finance and tech sectors tend to offer more lucrative packages compared to academia or non-profit sectors.

Career Advancement

To increase your salary further from a Mid-level/Intermediate position, consider pursuing a Senior Applied Scientist role or transitioning into a leadership position such as a Team Lead or Manager. This often requires demonstrating strong leadership skills, a track record of successful projects, and the ability to drive strategic initiatives. Additionally, specializing in high-demand areas like deep learning, natural language processing, or computer vision can make you more valuable. Networking within the industry, attending conferences, and publishing research can also enhance your visibility and open up higher-paying opportunities.

Educational Requirements

Most Mid-level/Intermediate Applied Scientist roles require at least a Master's degree in a relevant field such as Computer Science, Data Science, Statistics, or a related discipline. A Ph.D. can be advantageous, especially for roles that involve research and development of new algorithms or models. Employers often look for candidates with a strong foundation in mathematics, statistics, and programming, as well as experience with machine learning frameworks and tools.

Helpful Certifications

While not always mandatory, certain certifications can bolster your credentials and demonstrate expertise in specific areas. Certifications from recognized institutions or platforms, such as the Certified Data Scientist (CDS) or TensorFlow Developer Certificate, can be beneficial. Additionally, completing courses from platforms like Coursera, edX, or Udacity in machine learning, data science, or AI can provide a competitive edge.

Experience Requirements

Typically, a Mid-level/Intermediate Applied Scientist position requires 3-5 years of relevant experience. This experience should include hands-on work with machine learning models, data analysis, and software development. Experience in deploying models to production, working with large datasets, and collaborating in cross-functional teams is often highly valued. Demonstrating a history of successful projects and the ability to solve complex problems is crucial.

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