Salary for Executive-level / Director Associate in United States during 2024

Salary details

The average executive-level / director Associate salary lies between USD 74,670 and USD 147,500 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 Executive-level / Director Associate roles

The three most common job tag items assiciated with executive-level / director Associate job listings are Finance, Python 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:

Finance | 28 jobs Python | 25 jobs Engineering | 21 jobs Banking | 17 jobs Machine Learning | 16 jobs Excel | 16 jobs Data management | 16 jobs Research | 15 jobs Data governance | 15 jobs SQL | 14 jobs Data analysis | 12 jobs Computer Science | 12 jobs AWS | 9 jobs Security | 9 jobs Architecture | 9 jobs Data quality | 9 jobs Big Data | 8 jobs Tableau | 8 jobs Pipelines | 8 jobs ETL | 7 jobs

Top 20 Job Perks/Benefits for Executive-level / Director Associate roles

The three most common job benefits and perks assiciated with executive-level / director Associate job listings are Career development, Flex vacation and Health care. 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 | 28 jobs Flex vacation | 13 jobs Health care | 13 jobs Flex hours | 12 jobs Wellness | 7 jobs Equity / stock options | 6 jobs Competitive pay | 6 jobs Salary bonus | 5 jobs Parental leave | 4 jobs Startup environment | 3 jobs Transparency | 3 jobs Team events | 3 jobs Medical leave | 3 jobs Insurance | 3 jobs Conferences | 2 jobs Signing bonus | 1 jobs Relocation support | 1 jobs

Salary Composition

In the United States, the salary composition for an executive-level or director associate role in AI/ML/Data Science typically includes a combination of a fixed base salary, performance-based bonuses, and additional remuneration such as stock options or equity, especially in tech companies. The base salary often constitutes the largest portion, ranging from 60% to 80% of the total compensation package. Bonuses can vary significantly depending on the company's performance and individual achievements, usually accounting for 10% to 20% of the total salary. Additional remuneration, such as stock options, is more common in larger tech companies or startups and can make up 10% to 20% of the total compensation. 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. Industry-wise, tech and finance sectors often offer higher compensation compared to healthcare or education.

Increasing Salary

To increase your salary further from this position, consider the following strategies:

• Skill Enhancement: Continuously update your technical skills and knowledge in AI/ML, as the field is rapidly evolving. Specializing in emerging areas like deep learning, natural language processing, or AI ethics can make you more valuable.
• Leadership Development: Strengthen your leadership and management skills. Taking on more responsibilities, leading larger teams, or managing cross-functional projects can position you for higher-level roles.
• Networking: Build a strong professional network within the industry. Attend conferences, join professional organizations, and engage with thought leaders to increase your visibility and opportunities.
• Performance Excellence: Consistently exceed performance expectations and demonstrate your impact on the company's bottom line. This can lead to promotions or salary negotiations.
• Explore Opportunities: Consider opportunities in different regions or industries that may offer higher compensation. Transitioning to a larger company or a high-growth startup can also provide salary growth.

Educational Requirements

For an executive-level or director associate role in AI/ML/Data Science, a strong educational background is typically required. Most candidates hold at least a master's degree in a relevant field such as computer science, data science, statistics, or engineering. A Ph.D. can be advantageous, especially for roles that require deep technical expertise or research experience. Additionally, an MBA or a degree in management can be beneficial for those focusing on the business and strategic aspects of the role.

Helpful Certificates

While not always mandatory, certain certifications can enhance your qualifications and demonstrate your expertise. Some valuable certifications include:

• Certified Data Scientist (CDS): Offered by various organizations, this certification validates your data science skills and knowledge.
• AWS Certified Machine Learning – Specialty: Demonstrates your ability to design, implement, and maintain machine learning solutions on the AWS platform.
• Google Professional Machine Learning Engineer: Validates your proficiency in designing, building, and productionizing ML models using Google Cloud technologies.
• Microsoft Certified: Azure AI Engineer Associate: Shows your skills in using Azure AI services to build and integrate AI solutions.

Experience Requirements

Typically, candidates for this role have extensive experience in the field, often ranging from 8 to 15 years. This includes hands-on experience with AI/ML technologies, data analysis, and project management. Experience in leading teams, managing large-scale projects, and strategic decision-making is crucial. A proven track record of successful AI/ML implementations and the ability to translate complex technical concepts into business strategies are highly valued.

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