Salary for Executive-level / Director Associate during 2024

Salary details

The average executive-level / director Associate salary lies between USD 90,000 and USD 140,000 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: Nov. 10, 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 | 27 jobs Python | 23 jobs Engineering | 19 jobs Banking | 17 jobs Excel | 16 jobs Machine Learning | 15 jobs SQL | 13 jobs Research | 13 jobs Data management | 13 jobs Data governance | 13 jobs Data analysis | 10 jobs Computer Science | 10 jobs Tableau | 8 jobs Architecture | 8 jobs ETL | 7 jobs Big Data | 7 jobs AWS | 7 jobs Pipelines | 7 jobs Data quality | 7 jobs Privacy | 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 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 | 25 jobs Flex vacation | 13 jobs Flex hours | 12 jobs Health care | 12 jobs Wellness | 7 jobs Competitive pay | 5 jobs Equity / stock options | 4 jobs Parental leave | 3 jobs Startup environment | 3 jobs Transparency | 3 jobs Team events | 3 jobs Insurance | 3 jobs Salary bonus | 3 jobs Conferences | 2 jobs Medical leave | 2 jobs

Salary Composition

The salary for an Executive-level or Director Associate position in AI/ML/Data Science typically comprises a base salary, performance bonuses, and additional remuneration such as stock options or profit-sharing. The base salary is often the largest component, providing a stable income. Bonuses are usually tied to individual or company performance and can vary significantly. In tech hubs like Silicon Valley, stock options or equity can form a substantial part of the compensation package, especially in startups or high-growth companies. In contrast, larger, more established companies might offer more in terms of bonuses and less in equity. Regional differences also play a role; for instance, salaries in North America tend to be higher than in other regions, reflecting the cost of living and demand for talent. Industry-wise, tech and finance sectors often offer higher compensation compared to academia or non-profit organizations.

Increasing Salary

To increase your salary from this position, consider pursuing further specialization or leadership roles. This could involve taking on more strategic responsibilities, such as overseeing larger teams or managing cross-functional projects. Networking within the industry and building a strong personal brand can also open doors to higher-paying opportunities. Additionally, staying updated with the latest trends and technologies in AI/ML can make you more valuable to your organization. Pursuing advanced certifications or an executive MBA might also enhance your qualifications and bargaining power for a higher salary.

Educational Requirements

Most executive-level positions in AI/ML/Data Science require at least a master's degree in a related field such as computer science, data science, or engineering. A Ph.D. can be advantageous, especially for roles that involve significant research components or are within academia. However, practical experience and a proven track record in managing AI/ML projects can sometimes outweigh formal educational credentials, particularly in fast-paced tech environments.

Helpful Certifications

While not always mandatory, certain certifications can bolster your credentials. Certifications such as the Certified Analytics Professional (CAP), TensorFlow Developer Certificate, or AWS Certified Machine Learning can demonstrate your technical expertise. Leadership and management certifications, like those from PMI or Scrum Alliance, can also be beneficial, especially if your role involves overseeing projects or teams.

Required Experience

Typically, a minimum of 8-10 years of experience in AI/ML or data science is expected for executive-level roles. This experience should include a mix of technical expertise and leadership responsibilities. Experience in managing teams, developing and deploying AI/ML models, and strategic decision-making are crucial. A background in a specific industry, such as finance, healthcare, or technology, can also be advantageous, depending on the company's focus.

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