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: Dec. 15, 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 | 870 jobs SQL | 689 jobs Power BI | 476 jobs Tableau | 454 jobs Python | 446 jobs Computer Science | 367 jobs Engineering | 332 jobs ETL | 326 jobs Statistics | 318 jobs Data visualization | 284 jobs Data analysis | 277 jobs Excel | 252 jobs R | 234 jobs Data Analytics | 216 jobs Finance | 200 jobs Agile | 192 jobs Security | 183 jobs Mathematics | 182 jobs Testing | 174 jobs Data warehouse | 173 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 | 521 jobs Health care | 312 jobs Competitive pay | 188 jobs Flex hours | 186 jobs Insurance | 157 jobs Flex vacation | 144 jobs Startup environment | 140 jobs Team events | 140 jobs Equity / stock options | 130 jobs Parental leave | 128 jobs Salary bonus | 125 jobs Medical leave | 121 jobs 401(k) matching | 116 jobs Wellness | 108 jobs Unlimited paid time off | 35 jobs Flexible spending account | 30 jobs Gear | 25 jobs Home office stipend | 22 jobs Conferences | 20 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.

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