Salary for Senior-level / Expert Associate in United States during 2024

Salary details

The average senior-level / expert Associate salary lies between USD 81,000 and USD 144,900 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

Top 20 Job Tags for Senior-level / Expert Associate roles

The three most common job tag items assiciated with senior-level / expert Associate job listings are Python, SQL and Engineering. 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 | 786 jobs SQL | 688 jobs Engineering | 683 jobs Machine Learning | 490 jobs Data Analytics | 474 jobs Data management | 420 jobs Statistics | 414 jobs Agile | 391 jobs Computer Science | 374 jobs AWS | 366 jobs Research | 315 jobs Banking | 312 jobs Tableau | 307 jobs Business Intelligence | 306 jobs Architecture | 282 jobs Data analysis | 282 jobs Mathematics | 279 jobs Testing | 278 jobs Spark | 263 jobs Finance | 263 jobs

Top 20 Job Perks/Benefits for Senior-level / Expert Associate roles

The three most common job benefits and perks assiciated with senior-level / expert Associate job listings are Career development, Health care and Competitive pay. 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 | 889 jobs Health care | 405 jobs Competitive pay | 309 jobs Wellness | 244 jobs Flex hours | 199 jobs Team events | 155 jobs Startup environment | 152 jobs Flex vacation | 98 jobs Equity / stock options | 94 jobs Salary bonus | 84 jobs Parental leave | 81 jobs Medical leave | 62 jobs Relocation support | 60 jobs Insurance | 55 jobs Transparency | 47 jobs Conferences | 31 jobs Home office stipend | 20 jobs 401(k) matching | 19 jobs Flexible spending account | 15 jobs Gear | 13 jobs

Salary Composition

In the United States, the salary composition for a Senior-level or Expert Associate role in AI/ML/Data Science typically includes a combination of base salary, bonuses, and additional remuneration such as stock options or equity. The base salary is often the largest component, accounting for approximately 70-80% of the total compensation package. Bonuses, which can be performance-based or company-wide, might contribute around 10-20%. Additional remuneration, such as stock options, equity, or other benefits, can make up the remaining 5-10%.

The composition can vary significantly depending on the region, industry, and company size. For instance, tech hubs like Silicon Valley or New York City might offer higher base salaries and more substantial equity packages. In contrast, companies in the Midwest or South might offer lower base salaries but compensate with a higher percentage of bonuses. Large tech companies or financial institutions often provide more comprehensive compensation packages compared to startups or smaller firms.

Increasing Salary

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

• Specialization: Develop expertise in a niche area of AI/ML, such as natural language processing, computer vision, or reinforcement learning. Specialized skills are often in high demand and can command higher salaries.

• Leadership Roles: Transition into leadership or managerial roles, such as a team lead or director of data science. These positions typically offer higher compensation due to increased responsibilities.

• Continuous Learning: Stay updated with the latest technologies and methodologies in AI/ML. Attending workshops, conferences, and pursuing advanced certifications can enhance your skill set and marketability.

• Networking: Build a strong professional network within the industry. Networking can lead to new opportunities and insights into higher-paying roles.

• Negotiation Skills: Improve your negotiation skills to better advocate for higher compensation during job offers or performance reviews.

Educational Requirements

Most senior-level positions in AI/ML/Data Science require at least a master's degree in a related field such as computer science, data science, statistics, or mathematics. A Ph.D. is often preferred, especially for roles that involve research or advanced algorithm development. Candidates with a strong academic background in machine learning, artificial intelligence, or data analytics are highly sought after.

Helpful Certifications

While not always mandatory, certain certifications can enhance your credentials and demonstrate 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 knowledge, making you a more attractive candidate to potential employers.

Required Experience

Typically, a senior-level role in AI/ML/Data Science requires 5-10 years of relevant experience. This experience should include hands-on work with machine learning models, data analysis, and software development. Experience in leading projects, managing teams, or working in cross-functional environments is also highly valued. Demonstrated success in deploying AI/ML solutions in real-world applications can significantly bolster your candidacy.

Related salaries

Want to contribute?