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

Salary details

The average mid-level / intermediate Associate salary lies between USD 95,425 and USD 171,350 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. 10, 2024

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 | 2237 jobs Engineering | 1882 jobs SQL | 1632 jobs Machine Learning | 1470 jobs Computer Science | 1459 jobs Statistics | 1419 jobs Research | 1398 jobs R | 1032 jobs Mathematics | 954 jobs Testing | 890 jobs Data management | 841 jobs Data analysis | 826 jobs Agile | 793 jobs AWS | 763 jobs Security | 762 jobs Finance | 758 jobs Data Analytics | 749 jobs Excel | 747 jobs Tableau | 707 jobs Architecture | 688 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 | 2426 jobs Health care | 1079 jobs Flex hours | 990 jobs Team events | 733 jobs Competitive pay | 656 jobs Startup environment | 606 jobs Insurance | 494 jobs Flex vacation | 488 jobs Equity / stock options | 479 jobs Wellness | 467 jobs Parental leave | 402 jobs Salary bonus | 400 jobs Medical leave | 325 jobs Conferences | 215 jobs Relocation support | 215 jobs Transparency | 181 jobs 401(k) matching | 176 jobs Fitness / gym | 120 jobs Home office stipend | 74 jobs Unlimited paid time off | 67 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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