Salary for Executive-level / Director Manager during 2024

Salary details

The average executive-level / director Manager salary lies between USD 130,880 and USD 194,760 globally. 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.

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 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 | 108 jobs Machine Learning | 97 jobs Banking | 80 jobs Research | 64 jobs Agile | 64 jobs Python | 62 jobs Architecture | 58 jobs Finance | 54 jobs Data management | 54 jobs Computer Science | 54 jobs SQL | 51 jobs Data quality | 50 jobs Data Analytics | 49 jobs Statistics | 49 jobs Security | 46 jobs AWS | 44 jobs Mathematics | 44 jobs Excel | 43 jobs Consulting | 42 jobs Data governance | 41 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 | 153 jobs Health care | 112 jobs Competitive pay | 105 jobs Wellness | 84 jobs Insurance | 40 jobs Flex hours | 39 jobs Startup environment | 35 jobs Team events | 35 jobs Medical leave | 35 jobs Transparency | 24 jobs Salary bonus | 24 jobs Equity / stock options | 20 jobs Parental leave | 20 jobs Flex vacation | 19 jobs Relocation support | 11 jobs Gear | 6 jobs Travel | 5 jobs Unlimited paid time off | 5 jobs 401(k) matching | 4 jobs Conferences | 3 jobs

Salary Composition

The salary for an executive-level or director manager position in AI/ML/Data Science typically comprises a base salary, performance bonuses, and additional remuneration such as stock options or equity, especially in tech companies. The base salary is often the largest component, providing a stable income. Performance bonuses are usually tied to individual, team, or company performance metrics and can vary significantly. Additional remuneration like stock options is more common in startups or large tech firms, offering potential long-term financial benefits.

Regional differences can affect salary composition. For instance, positions in tech hubs like Silicon Valley or New York may offer higher base salaries and more substantial equity packages compared to other regions. Industry also plays a role; finance and healthcare sectors might offer higher bonuses due to the critical nature of data-driven decision-making in these fields. Company size can influence salary structure, with larger companies often providing more comprehensive benefits and smaller companies offering more equity to compensate for lower base salaries.

Increasing Salary

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

• Skill Enhancement: Continuously update your technical and managerial skills. Specializing in emerging AI/ML technologies or methodologies can make you more valuable.
• Networking: Build a strong professional network. Engaging with industry leaders and participating in conferences can open up higher-paying opportunities.
• Leadership Roles: Seek roles with greater responsibility, such as leading larger teams or managing cross-functional projects.
• Negotiation: Improve your negotiation skills to better advocate for higher compensation during performance reviews or when switching jobs.
• Industry Shift: Consider moving to industries with higher pay scales for AI/ML roles, such as finance or healthcare.

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 techniques. An MBA can also be beneficial, particularly for roles that require strong business acumen and leadership skills.

Helpful Certifications

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

• Certified Analytics Professional (CAP): Validates your ability to transform data into valuable insights.
• AWS Certified Machine Learning – Specialty: Demonstrates proficiency in using AWS for machine learning tasks.
• Google Professional Machine Learning Engineer: Shows expertise in designing and building machine learning models on Google Cloud.
• Microsoft Certified: Azure AI Engineer Associate: Highlights skills in using Azure for AI solutions.

Required Experience

Typically, these roles require extensive experience in AI/ML or data science, often 8-10 years or more. This experience should include a mix of technical expertise and leadership roles, such as managing data science teams or leading significant AI projects. Experience in strategic planning and execution, as well as a proven track record of driving business results through data-driven insights, is crucial.

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