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

Salary details

The average executive-level / director Manager salary lies between USD 130,880 and USD 180,000 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 Executive-level / Director Manager roles

The three most common job tag items assiciated with executive-level / director Manager job listings are Engineering, Machine Learning and Banking. 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:

Engineering | 97 jobs Machine Learning | 81 jobs Banking | 68 jobs Agile | 55 jobs Python | 53 jobs Architecture | 52 jobs Research | 51 jobs Data management | 49 jobs Finance | 48 jobs Computer Science | 47 jobs SQL | 44 jobs Data Analytics | 41 jobs Security | 40 jobs Data quality | 40 jobs AWS | 39 jobs Statistics | 38 jobs Mathematics | 38 jobs Consulting | 36 jobs Excel | 35 jobs Data governance | 32 jobs

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

The three most common job benefits and perks assiciated with executive-level / director Manager 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 | 128 jobs Health care | 95 jobs Competitive pay | 91 jobs Wellness | 72 jobs Flex hours | 32 jobs Startup environment | 31 jobs Insurance | 29 jobs Team events | 28 jobs Medical leave | 25 jobs Transparency | 18 jobs Equity / stock options | 17 jobs Parental leave | 17 jobs Salary bonus | 17 jobs Flex vacation | 13 jobs Relocation support | 11 jobs Unlimited paid time off | 5 jobs Travel | 4 jobs Gear | 4 jobs 401(k) matching | 3 jobs Conferences | 3 jobs

Salary Composition

In the United States, the salary composition for an executive-level or director manager 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 fixed base salary often constitutes the majority of the total compensation package, ranging from 60% to 80%. Bonuses can vary significantly depending on the company's performance and individual achievements, usually accounting for 10% to 20% of the total compensation. Additional remuneration, such as stock options, can be a significant part of the package, particularly in startups or large tech firms, and may range from 10% to 30%.

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 variations are notable as well, with tech companies generally offering higher compensation compared to sectors like healthcare or finance. Company size can influence salary composition, with larger companies often providing more comprehensive bonus structures and equity options.

Increasing Salary

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

• Expand Your Skill Set: Continuously update your technical and managerial skills. Specializing in emerging AI/ML technologies or acquiring expertise in data-driven decision-making can make you more valuable.
• Pursue Advanced Education: An MBA or a specialized master's degree in AI/ML can enhance your qualifications and open up higher-paying opportunities.
• Network and Build Relationships: Engage with industry leaders and participate in conferences or seminars. Networking can lead to new opportunities and insights into higher-paying roles.
• Seek Leadership Roles: Aim for positions with greater responsibility, such as VP or C-level roles, which typically come with higher compensation.
• Negotiate Effectively: When offered a new position or during performance reviews, negotiate for higher pay, better bonuses, or more equity.

Educational Requirements

Most executive-level positions in AI/ML/Data Science require at least a bachelor's degree in a related field such as computer science, data science, or engineering. However, a master's degree or Ph.D. is often preferred, especially for roles that demand a deep understanding of complex algorithms and data analysis. An MBA can also be beneficial for those looking to move into more strategic and leadership-focused roles.

Helpful Certifications

While not always mandatory, certain certifications can enhance your credibility and demonstrate your commitment to the field. Some valuable certifications include:

• Certified Analytics Professional (CAP)
• Google Professional Machine Learning Engineer
• AWS Certified Machine Learning – Specialty
• Microsoft Certified: Azure AI Engineer Associate

These certifications can help validate your skills and knowledge, making you a more attractive candidate for higher-level positions.

Required Experience

Typically, candidates for executive-level roles in AI/ML/Data Science are expected to have at least 10-15 years of experience in the field. This experience should include a mix of technical expertise in AI/ML and data science, as well as leadership and management experience. Experience in leading cross-functional teams, managing large-scale projects, and driving strategic initiatives is highly valued.

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