Salary for Mid-level / Intermediate Business Intelligence in United States during 2024

Salary details

The average mid-level / intermediate Business Intelligence salary lies between USD 95,000 and USD 156,800 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 Mid-level / Intermediate Business Intelligence roles

The three most common job tag items assiciated with mid-level / intermediate Business Intelligence job listings are Business Intelligence, SQL and Power BI. 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 | 827 jobs SQL | 659 jobs Power BI | 455 jobs Tableau | 437 jobs Python | 423 jobs Computer Science | 345 jobs Engineering | 317 jobs ETL | 307 jobs Statistics | 303 jobs Data visualization | 274 jobs Data analysis | 262 jobs Excel | 243 jobs R | 223 jobs Data Analytics | 203 jobs Finance | 194 jobs Agile | 180 jobs Security | 174 jobs Mathematics | 173 jobs Data warehouse | 165 jobs Testing | 160 jobs

Top 20 Job Perks/Benefits for Mid-level / Intermediate Business Intelligence roles

The three most common job benefits and perks assiciated with mid-level / intermediate 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 | 487 jobs Health care | 298 jobs Competitive pay | 181 jobs Flex hours | 180 jobs Insurance | 150 jobs Flex vacation | 140 jobs Startup environment | 135 jobs Team events | 132 jobs Equity / stock options | 122 jobs Parental leave | 122 jobs Salary bonus | 120 jobs Medical leave | 116 jobs 401(k) matching | 112 jobs Wellness | 105 jobs Unlimited paid time off | 33 jobs Flexible spending account | 29 jobs Gear | 25 jobs Home office stipend | 22 jobs Conferences | 19 jobs Fitness / gym | 17 jobs

Salary Composition

In the United States, the salary composition for a Mid-level/Intermediate Business Intelligence professional in AI/ML/Data Science can vary significantly based on factors such as region, industry, and company size. Typically, the salary is divided into three main components: base salary, bonuses, and additional remuneration.

• Base Salary: This is the fixed annual amount and usually constitutes the largest portion of the total compensation package. In tech hubs like San Francisco or New York, the base salary might be higher due to the cost of living and competitive job market.

• Bonuses: These are performance-based and can vary widely. In industries like finance or tech, bonuses can be substantial, sometimes ranging from 10% to 20% of the base salary. Companies may offer annual bonuses, sign-on bonuses, or even stock options as part of the compensation package.

• Additional Remuneration: This includes benefits such as health insurance, retirement contributions, and other perks like stock options or equity, especially in startups or large tech companies. The value of these benefits can significantly enhance the overall compensation package.

Increasing Salary

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

• Skill Enhancement: Continuously update your skills in emerging AI/ML technologies and tools. Specializing in niche areas like deep learning, natural language processing, or computer vision can make you more valuable.

• Advanced Education: Pursuing a master's degree or a Ph.D. in a related field can open doors to higher-paying roles and leadership positions.

• Networking: Building a strong professional network can lead to opportunities in higher-paying companies or roles. Attend industry conferences, join professional groups, and engage in online forums.

• Leadership Roles: Aim for roles that involve team leadership or project management, as these often come with higher compensation.

Educational Requirements

Most positions 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, many employers prefer candidates with a master's degree or higher, especially for more advanced roles. A strong foundation in programming, data analysis, and machine learning principles is essential.

Helpful Certifications

Certifications can enhance your resume and demonstrate your expertise to potential employers. Some valuable certifications include:

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

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

Required Experience

Typically, a Mid-level/Intermediate position requires 3-5 years of experience in business intelligence, data analysis, or a related field. Experience with data visualization tools, machine learning frameworks, and programming languages like Python or R is often necessary. Demonstrated experience in handling large datasets and deriving actionable insights is also crucial.

Related salaries

Want to contribute?