Salary for Executive-level / Director Business Intelligence during 2024

Salary details

The average executive-level / director Business Intelligence salary lies between USD 150,000 and USD 230,000 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 Business Intelligence roles

The three most common job tag items assiciated with executive-level / director Business Intelligence job listings are Business Intelligence, SQL and Tableau. 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:

Business Intelligence | 130 jobs SQL | 74 jobs Tableau | 65 jobs Power BI | 65 jobs Computer Science | 56 jobs Python | 54 jobs Engineering | 52 jobs Data Analytics | 52 jobs Statistics | 46 jobs Data management | 41 jobs Data visualization | 39 jobs Finance | 36 jobs Data governance | 36 jobs Data quality | 36 jobs Data Warehousing | 34 jobs Excel | 33 jobs ETL | 31 jobs Security | 30 jobs Testing | 30 jobs Machine Learning | 28 jobs

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

The three most common job benefits and perks assiciated with executive-level / director Business Intelligence job listings are Career development, Startup environment 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 | 83 jobs Startup environment | 52 jobs Health care | 51 jobs Competitive pay | 31 jobs Salary bonus | 29 jobs Equity / stock options | 27 jobs Flex hours | 24 jobs Flex vacation | 24 jobs Wellness | 24 jobs Team events | 24 jobs Insurance | 21 jobs Parental leave | 20 jobs Fitness / gym | 16 jobs 401(k) matching | 13 jobs Medical leave | 13 jobs Transparency | 8 jobs Home office stipend | 5 jobs Unlimited paid time off | 3 jobs Fertility benefits | 3 jobs Travel | 2 jobs

Salary Composition

The salary for an Executive-level or Director of Business Intelligence 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 often forms the largest portion, ranging from 60% to 80% of the total compensation package. Performance bonuses can vary significantly, often between 10% to 30%, depending on the company's performance and individual achievements. Additional remuneration, such as stock options, is more common in larger tech firms or startups and can constitute 10% to 20% of the total package.

Regional differences also play a role; for instance, salaries in tech hubs like San Francisco or New York are generally higher than in other regions. Industry-wise, tech and finance sectors tend to offer more lucrative packages compared to healthcare or manufacturing. Company size can also influence salary composition, with larger companies often providing more comprehensive bonus structures and stock options.

Increasing Salary Further

To increase your salary beyond the median of USD 200,000, consider the following strategies:

• Expand Your Skill Set: Continuously update your skills in emerging AI/ML technologies and tools. Specializing in niche areas like deep learning or natural language processing can make you more valuable.
• Leadership Development: Enhance your leadership and management skills. Pursuing executive education programs or leadership workshops can prepare you for higher roles.
• Networking: Build a strong professional network. Engaging with industry leaders and participating in conferences can open up opportunities for higher-paying roles.
• Performance Excellence: Consistently exceed performance expectations. Demonstrating a track record of successful projects and initiatives can justify salary negotiations.
• Explore New Opportunities: Be open to opportunities in different regions or industries that may offer higher compensation.

Educational Requirements

Most executive-level roles 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, particularly for roles that require strong business acumen and strategic decision-making.

Helpful Certifications

While not always mandatory, certain certifications can enhance your credibility and expertise in the field:

• Certified Analytics Professional (CAP): Validates your ability to transform data into valuable insights.
• Google Professional Machine Learning Engineer: Demonstrates proficiency in designing and implementing ML models on Google Cloud.
• AWS Certified Machine Learning – Specialty: Shows expertise in building, training, and deploying ML models on AWS.
• Data Science Council of America (DASCA) Certifications: Offers various levels of data science certifications that are recognized globally.

Required Experience

Typically, a minimum of 10-15 years of experience in data science, analytics, or a related field is required for an executive-level position. This experience should include a proven track record of leading data-driven projects, managing teams, and delivering business insights. Experience in strategic planning and decision-making is also crucial, as these roles often involve shaping the company's data strategy.

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