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

Salary details

The average mid-level / intermediate Associate salary lies between USD 95,000 and USD 172,300 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: Jan. 26, 2025

Salary trend

Top 20 Job Tags for Mid-level / Intermediate Associate roles

The three most common job tag items assiciated with mid-level / intermediate Associate job listings are Python, Engineering and SQL. 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:

Python | 2436 jobs Engineering | 2089 jobs SQL | 1730 jobs Machine Learning | 1614 jobs Computer Science | 1604 jobs Research | 1550 jobs Statistics | 1488 jobs R | 1172 jobs Mathematics | 1000 jobs Testing | 975 jobs Data management | 941 jobs Data analysis | 878 jobs Security | 876 jobs Agile | 841 jobs AWS | 805 jobs Excel | 787 jobs Data Analytics | 761 jobs Finance | 761 jobs Architecture | 738 jobs Pipelines | 681 jobs

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

The three most common job benefits and perks assiciated with mid-level / intermediate Associate job listings are Career development, Health care and Flex hours. 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 | 2770 jobs Health care | 1179 jobs Flex hours | 1174 jobs Team events | 812 jobs Competitive pay | 685 jobs Startup environment | 664 jobs Insurance | 604 jobs Flex vacation | 591 jobs Equity / stock options | 585 jobs Salary bonus | 473 jobs Parental leave | 472 jobs Wellness | 463 jobs Medical leave | 384 jobs Conferences | 258 jobs Relocation support | 234 jobs 401(k) matching | 207 jobs Transparency | 200 jobs Fitness / gym | 143 jobs Home office stipend | 84 jobs Flexible spending account | 83 jobs

Salary Composition

In the United States, the salary composition for a mid-level AI/ML/Data Science role typically includes 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 constitutes the majority of the total compensation package. Performance bonuses can vary significantly depending on the company’s policy and individual performance, often ranging from 10% to 20% of the base salary. Additional remuneration, like stock options, is more common in larger tech companies or startups and can be a significant part of the compensation, especially in high-growth industries. 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.

Increasing Salary

To increase your salary from a mid-level position, consider the following strategies:

• Skill Enhancement: Continuously update your skills in emerging technologies and tools in AI/ML, such as deep learning frameworks, cloud computing, and big data technologies.
• Advanced Education: Pursuing a master's degree or a Ph.D. in a relevant field can open up higher-paying opportunities.
• Leadership Roles: Transitioning into roles that involve team leadership or project management can lead to higher compensation.
• Industry Shift: Moving to industries that pay higher for AI/ML expertise, such as finance or healthcare, can also be beneficial.
• Networking: Building a strong professional network can lead to opportunities in higher-paying companies or roles.

Educational Requirements

Most mid-level AI/ML/Data Science positions require at least a bachelor's degree in a related field such as computer science, data science, statistics, or engineering. However, a master's degree is often preferred and can be a significant advantage. Some roles may also require specific coursework or experience in machine learning, data analysis, and programming languages like Python or R.

Helpful Certifications

While not always mandatory, certain certifications can enhance your profile and demonstrate your expertise:

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

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

Experience Requirements

Typically, a mid-level position requires 3 to 5 years of relevant experience in data science or machine learning roles. This experience should include hands-on work with data analysis, model building, and deployment. Experience in specific industries or with particular types of data (e.g., time series, image data) can also be advantageous.

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