Salary for Mid-level / Intermediate BI Developer in United States during 2024

Salary details

The average mid-level / intermediate BI Developer salary lies between USD 64,900 and USD 120,525 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

Salary trend

Top 20 Job Tags for Mid-level / Intermediate BI Developer roles

The three most common job tag items assiciated with mid-level / intermediate BI Developer job listings are SQL, Power BI and ETL. 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:

SQL | 296 jobs Power BI | 274 jobs ETL | 162 jobs Business Intelligence | 150 jobs Computer Science | 130 jobs Security | 129 jobs Tableau | 115 jobs Azure | 114 jobs Agile | 103 jobs Data analysis | 100 jobs Data Analytics | 97 jobs Engineering | 93 jobs Data visualization | 93 jobs Python | 75 jobs SSIS | 75 jobs Testing | 72 jobs DevOps | 70 jobs RDBMS | 65 jobs Pipelines | 57 jobs Data quality | 57 jobs

Top 20 Job Perks/Benefits for Mid-level / Intermediate BI Developer roles

The three most common job benefits and perks assiciated with mid-level / intermediate BI Developer job listings are Career development, Health care and Flex hours. 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 | 220 jobs Health care | 113 jobs Flex hours | 95 jobs Insurance | 63 jobs Flex vacation | 56 jobs Team events | 52 jobs Salary bonus | 39 jobs Startup environment | 37 jobs Competitive pay | 36 jobs Flexible spending account | 33 jobs Equity / stock options | 27 jobs Parental leave | 22 jobs 401(k) matching | 18 jobs Wellness | 17 jobs Fitness / gym | 15 jobs Medical leave | 15 jobs Home office stipend | 10 jobs Signing bonus | 8 jobs Transparency | 7 jobs Conferences | 5 jobs

Salary Composition

In the United States, the salary composition for a mid-level AI/ML/Data Science role can vary significantly based on factors such as region, industry, and company size. Typically, the salary is composed of a fixed base salary, which forms the bulk of the compensation package. This base salary can range from 70% to 90% of the total compensation. Bonuses, which can be performance-based or company-wide, often account for 10% to 20% of the total package. Additional remuneration may include stock options, especially in tech companies or startups, and other benefits like health insurance, retirement contributions, and professional development allowances. In tech hubs like Silicon Valley or New York, the base salary might be higher, but the cost of living is also elevated. Conversely, in regions with a lower cost of living, the base salary might be slightly lower, but the overall quality of life could be better.

Increasing Salary Potential

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 relevant field can open doors to higher-paying roles.
• Leadership Roles: Transitioning into a leadership or managerial role can significantly boost your salary. This might involve leading a team of data scientists or managing projects.
• Networking: Building a strong professional network can lead to opportunities in higher-paying companies or industries.
• Industry Shift: Some industries, like finance or healthcare, may offer higher salaries for AI/ML roles compared to others.

Educational Requirements

Most mid-level AI/ML/Data Science positions require at least a bachelor's degree in a related field such as computer science, data science, mathematics, or statistics. However, many employers prefer candidates with a master's degree or higher, especially for roles that involve complex problem-solving and advanced algorithm development. A strong foundation in programming, data structures, and algorithms is essential, along with a good understanding of machine learning principles and statistical analysis.

Helpful Certifications

While not always mandatory, certain certifications can enhance your credibility and demonstrate your commitment to the field. Some valuable certifications include:

• Certified Data Scientist (CDS)
• TensorFlow Developer Certificate
• AWS Certified Machine Learning – Specialty
• Microsoft Certified: Azure AI Engineer Associate
• Google Professional Machine Learning Engineer

These certifications can help you stand out in a competitive job market and may lead to better job opportunities and salary prospects.

Required Experience

Typically, a mid-level AI/ML/Data Science role requires 3 to 5 years of relevant experience. This experience should include hands-on work with data analysis, machine learning model development, and deployment. Experience in handling large datasets, using data visualization tools, and working with cloud platforms is often expected. Additionally, experience in a specific industry can be advantageous, as it provides domain knowledge that can be critical for certain roles.

Related salaries

Want to contribute?