Salary for Senior-level / Expert Business Intelligence in United States during 2024

Salary details

The average senior-level / expert Business Intelligence salary lies between USD 105,800 and USD 182,800 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: Dec. 22, 2024

Top 20 Job Tags for Senior-level / Expert Business Intelligence roles

The three most common job tag items assiciated with senior-level / expert Business Intelligence job listings are Business Intelligence, SQL and Python. 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 | 1239 jobs SQL | 1016 jobs Python | 653 jobs Tableau | 651 jobs Power BI | 626 jobs Engineering | 519 jobs Computer Science | 513 jobs ETL | 479 jobs Statistics | 456 jobs Data analysis | 410 jobs Data visualization | 389 jobs Finance | 336 jobs R | 300 jobs Data warehouse | 292 jobs Excel | 287 jobs Data Analytics | 286 jobs Architecture | 276 jobs Security | 275 jobs Data Warehousing | 261 jobs Agile | 260 jobs

Top 20 Job Perks/Benefits for Senior-level / Expert Business Intelligence roles

The three most common job benefits and perks assiciated with senior-level / expert Business Intelligence 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 | 738 jobs Health care | 491 jobs Competitive pay | 306 jobs Equity / stock options | 289 jobs Flex hours | 279 jobs Insurance | 254 jobs Parental leave | 224 jobs Team events | 221 jobs Salary bonus | 213 jobs Flex vacation | 212 jobs Medical leave | 208 jobs Startup environment | 197 jobs Wellness | 180 jobs 401(k) matching | 139 jobs Gear | 49 jobs Flexible spending account | 41 jobs Transparency | 35 jobs Fitness / gym | 33 jobs Home office stipend | 33 jobs Unlimited paid time off | 30 jobs

Salary Composition

In the United States, the salary composition for a Senior-level or Expert Business Intelligence 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 70% to 85%. Bonuses can vary significantly depending on the company and industry, generally accounting for 10% to 20% of the total compensation. Additional remuneration, such as stock options, profit-sharing, or other incentives, can make up the remaining 5% to 10%.

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 markets. Industry-wise, tech companies, financial services, and healthcare often offer more lucrative packages compared to other sectors. Larger companies may provide more comprehensive benefits and higher bonuses, while smaller companies might offer more equity as part of the compensation.

Increasing Salary Further

To increase your salary further from a Senior-level position, consider the following strategies:

• Specialization: Develop expertise in a niche area within AI/ML or Data Science that is in high demand, such as natural language processing, computer vision, or AI ethics.
• Leadership Roles: Transition into leadership or managerial roles, such as a Director of Data Science or Chief Data Officer, which typically come with higher compensation.
• Continuous Learning: Stay updated with the latest technologies and methodologies in AI/ML. Pursuing advanced certifications or a master's degree in a related field can also enhance your qualifications.
• Networking: Build a strong professional network to learn about higher-paying opportunities and gain insights into industry trends.
• Negotiation Skills: Improve your negotiation skills to better advocate for higher pay during performance reviews or when considering new job offers.

Educational Requirements

Most Senior-level Business Intelligence roles in AI/ML/Data Science require at least a bachelor's degree in a related field such as Computer Science, Data Science, Statistics, or Mathematics. However, a master's degree or Ph.D. is often preferred, especially for roles that involve complex data analysis or the development of advanced machine learning models. An MBA with a focus on data analytics can also be beneficial for those looking to combine business acumen with technical expertise.

Helpful Certifications

Several certifications can enhance your credentials and demonstrate your expertise in AI/ML and Data Science:

• Certified Analytics Professional (CAP): Validates your ability to transform data into valuable insights.
• Google Professional Machine Learning Engineer: Demonstrates proficiency in designing, building, and productionizing ML models.
• Microsoft Certified: Azure Data Scientist Associate: Focuses on using Azure services to build and deploy machine learning models.
• AWS Certified Machine Learning – Specialty: Validates expertise in building, training, and deploying ML models on AWS.

Required Experience

Typically, a Senior-level position in this field requires at least 5 to 10 years of experience in data analysis, business intelligence, or a related area. Experience should include hands-on work with data modeling, statistical analysis, and machine learning algorithms. Additionally, experience in leading projects, managing teams, and collaborating with cross-functional stakeholders is often required.

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