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: Nov. 17, 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 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 | 1157 jobs SQL | 944 jobs Tableau | 610 jobs Python | 597 jobs Power BI | 580 jobs Engineering | 473 jobs Computer Science | 467 jobs ETL | 442 jobs Statistics | 414 jobs Data analysis | 378 jobs Data visualization | 364 jobs Finance | 316 jobs R | 278 jobs Data warehouse | 273 jobs Excel | 271 jobs Data Analytics | 262 jobs Architecture | 256 jobs Security | 254 jobs Data Warehousing | 247 jobs AWS | 241 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 | 686 jobs Health care | 456 jobs Competitive pay | 284 jobs Equity / stock options | 275 jobs Flex hours | 263 jobs Insurance | 233 jobs Parental leave | 212 jobs Team events | 208 jobs Flex vacation | 196 jobs Medical leave | 195 jobs Salary bonus | 195 jobs Startup environment | 186 jobs Wellness | 168 jobs 401(k) matching | 131 jobs Gear | 46 jobs Flexible spending account | 41 jobs Fitness / gym | 33 jobs Transparency | 33 jobs Home office stipend | 33 jobs Conferences | 29 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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