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

Salary details

The average executive-level / director Data Analyst salary lies between USD 80,000 and USD 140,000 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. 24, 2024

Salary trend

Top 20 Job Tags for Executive-level / Director Data Analyst roles

The three most common job tag items assiciated with executive-level / director Data Analyst job listings are Excel, SQL and Data analysis. 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:

Excel | 31 jobs SQL | 30 jobs Data analysis | 30 jobs Research | 25 jobs Data Analytics | 25 jobs Python | 23 jobs Tableau | 20 jobs Statistics | 20 jobs Data quality | 18 jobs Testing | 16 jobs Finance | 15 jobs Power BI | 14 jobs Data visualization | 14 jobs Banking | 13 jobs Agile | 12 jobs Data management | 12 jobs Engineering | 11 jobs Data governance | 10 jobs Architecture | 8 jobs Snowflake | 8 jobs

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

The three most common job benefits and perks assiciated with executive-level / director Data Analyst 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 | 35 jobs Health care | 32 jobs Competitive pay | 31 jobs Wellness | 18 jobs Startup environment | 15 jobs Flex hours | 13 jobs Medical leave | 12 jobs Insurance | 10 jobs Transparency | 8 jobs Salary bonus | 8 jobs Parental leave | 6 jobs Team events | 5 jobs Flex vacation | 4 jobs Unlimited paid time off | 4 jobs 401(k) matching | 3 jobs Equity / stock options | 3 jobs Travel | 3 jobs Conferences | 1 jobs Flexible spending account | 1 jobs

Salary Composition

The salary for an Executive-level or Director Data Analyst in the AI/ML/Data Science field 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 based on the company's success and the individual's contribution. Additional remuneration, like stock options, is more common in tech companies or startups, offering potential long-term financial benefits.

Regional differences can also impact salary composition. For instance, positions in tech hubs like Silicon Valley or New York City might offer higher base salaries and more lucrative stock options due to the higher cost of living and competitive job market. Industry also plays a role; tech and finance sectors often provide higher compensation packages compared to other industries. Company size can influence salary composition as well, with larger companies typically offering more comprehensive benefits and bonuses.

Increasing Salary

To increase your salary from this position, consider pursuing further specialization or leadership roles. Specializing in a niche area of data science, such as machine learning engineering or data architecture, can make you more valuable. Additionally, seeking leadership roles that involve managing larger teams or more significant projects can lead to higher compensation. Networking within the industry and staying updated with the latest trends and technologies can also open up opportunities for advancement. Pursuing an MBA or executive education programs can enhance your leadership skills and make you a more attractive candidate for higher-paying roles.

Educational Requirements

Most executive-level or director positions in data science require at least a bachelor's degree in a related field such as computer science, statistics, mathematics, or engineering. However, a master's degree or Ph.D. is often preferred, especially for roles that involve complex data analysis and strategic decision-making. Advanced degrees provide a deeper understanding of data science principles and methodologies, which are crucial for high-level positions.

Helpful Certifications

Certifications can enhance your credentials and demonstrate your expertise in specific areas. Some valuable certifications include:

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

These certifications can validate your skills and knowledge, making you a more competitive candidate for executive roles.

Experience Requirements

Typically, executive-level or director positions require significant experience in data analysis, machine learning, or related fields. This often means at least 8-10 years of experience, with a proven track record of leading successful projects and teams. Experience in strategic planning, project management, and cross-functional collaboration is also highly valued. Demonstrating the ability to translate complex data insights into actionable business strategies is crucial for these roles.

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