Salary for Senior-level / Expert BI Analyst in United States during 2024

Salary details

The average senior-level / expert BI Analyst salary lies between USD 80,000 and USD 130,000 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 Senior-level / Expert BI Analyst roles

The three most common job tag items assiciated with senior-level / expert BI Analyst job listings are SQL, Power BI and Business Intelligence. 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 | 116 jobs Power BI | 97 jobs Business Intelligence | 77 jobs Tableau | 74 jobs Data analysis | 66 jobs Python | 61 jobs Excel | 55 jobs Statistics | 53 jobs Finance | 49 jobs Data visualization | 44 jobs Agile | 41 jobs Engineering | 40 jobs Data Analytics | 40 jobs R | 37 jobs ETL | 37 jobs Azure | 35 jobs Data quality | 35 jobs Security | 33 jobs Computer Science | 33 jobs KPIs | 30 jobs

Top 20 Job Perks/Benefits for Senior-level / Expert BI Analyst roles

The three most common job benefits and perks assiciated with senior-level / expert BI Analyst job listings are Career development, Flex hours and Health care. 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 | 71 jobs Flex hours | 36 jobs Health care | 33 jobs Startup environment | 28 jobs Competitive pay | 24 jobs Team events | 24 jobs Equity / stock options | 14 jobs Flex vacation | 14 jobs Insurance | 13 jobs Medical leave | 12 jobs Parental leave | 10 jobs 401(k) matching | 9 jobs Salary bonus | 7 jobs Relocation support | 5 jobs Wellness | 4 jobs Transparency | 4 jobs Home office stipend | 3 jobs Lunch / meals | 2 jobs Travel | 2 jobs Gear | 2 jobs

Salary Composition for Senior-level/Expert BI Analyst Roles

In the United States, the salary composition for a Senior-level or Expert BI Analyst in AI/ML/Data Science typically includes a combination of a fixed base salary, performance bonuses, and additional remuneration such as stock options or profit-sharing. The base salary often constitutes the majority of the total compensation package, ranging from 70% to 85%. Performance bonuses can vary significantly depending on the company and industry, often comprising 10% to 20% of the total compensation. Additional remuneration, such as stock options or profit-sharing, is more common in larger tech companies or startups and can make up 5% to 10% of the total package.

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 higher compensation packages compared to other sectors. Company size can also influence salary composition, with larger companies typically offering more comprehensive benefits and bonuses.

Steps to Increase Salary from a Senior-level/Expert BI Analyst Position

To increase your salary beyond the median of USD 100,000, consider the following strategies:

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

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

• Networking and Professional Visibility: Attend industry conferences, contribute to open-source projects, and publish articles or research papers. Building a strong professional network can lead to new opportunities and salary negotiations.

• Leadership Roles: Transitioning into managerial or leadership roles within your organization can significantly increase your earning potential.

• Negotiation Skills: Improve your negotiation skills to better advocate for salary increases during performance reviews or when switching jobs.

Educational Requirements for Senior-level/Expert BI Analyst Roles

Most Senior-level or Expert BI Analyst positions require at least a bachelor's degree in a related field such as Computer Science, Data Science, Statistics, Mathematics, or Information Technology. However, many employers prefer candidates with a master's degree or higher, especially for roles that involve complex data analysis and machine learning model development. A strong educational background provides a solid foundation in analytical thinking, statistical methods, and technical skills necessary for the role.

Helpful Certifications for BI Analysts in AI/ML/Data Science

Certifications can enhance your credentials and demonstrate expertise in specific areas. Some valuable certifications include:

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

Experience Requirements for Senior-level/Expert BI Analyst Roles

Typically, these roles require a minimum of 5 to 8 years of experience in business intelligence, data analysis, or a related field. Experience with data visualization tools (e.g., Tableau, Power BI), SQL, and programming languages (e.g., Python, R) is essential. Additionally, experience in managing projects, leading teams, or working in cross-functional environments can be advantageous.

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