BI Analyst Salary in 2023

Salary details

The average BI Analyst salary lies between USD 110,000 and USD 160,000 globally. 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.

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

Salary trend

Top 20 Job Tags for BI Analyst roles

The three most common job tag items assiciated with BI Analyst job listings are SQL, Business Intelligence and Power BI. Below you find a list of the 20 most occuring job tags in 2023 and the number of open jobs that where associated with them during that period:

SQL | 123 jobs Business Intelligence | 83 jobs Power BI | 79 jobs Tableau | 77 jobs Python | 60 jobs Finance | 54 jobs Statistics | 54 jobs Excel | 51 jobs Engineering | 49 jobs Data analysis | 48 jobs Data visualization | 46 jobs Computer Science | 40 jobs R | 38 jobs Data Analytics | 33 jobs Mathematics | 33 jobs ETL | 32 jobs Testing | 32 jobs E-commerce | 24 jobs Data warehouse | 24 jobs Looker | 23 jobs

Top 20 Job Perks/Benefits for BI Analyst roles

The three most common job benefits and perks assiciated with BI Analyst job listings are Career development, Startup environment and Health care. Below you find a list of the 20 most occuring job perks or benefits in 2023 and the number of open jobs that where offering them during that period:

Career development | 89 jobs Startup environment | 43 jobs Health care | 42 jobs Team events | 34 jobs Competitive pay | 32 jobs Flex hours | 26 jobs Flex vacation | 22 jobs Equity / stock options | 20 jobs Insurance | 19 jobs Salary bonus | 18 jobs Medical leave | 15 jobs Parental leave | 10 jobs Home office stipend | 10 jobs Wellness | 8 jobs Transparency | 8 jobs Unlimited paid time off | 8 jobs 401(k) matching | 5 jobs Relocation support | 5 jobs Conferences | 4 jobs Fertility benefits | 4 jobs

Salary Composition

The salary composition for a BI Analyst 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: a fixed base salary, a performance-based bonus, and additional remuneration such as stock options or benefits. In regions like the United States, particularly in tech hubs like Silicon Valley, the base salary might constitute around 70-80% of the total compensation package. Bonuses can range from 10-20%, often tied to individual or company performance metrics. Additional remuneration, which may include stock options, health benefits, and retirement contributions, can make up the remaining 5-10%. In smaller companies or startups, stock options might play a more significant role, whereas larger corporations might offer more substantial bonuses and benefits.

Steps to Increase Salary

To increase your salary from a BI Analyst position, consider the following strategies:

• Skill Enhancement: Continuously upgrade your skills in AI/ML and data science. Mastering advanced tools and techniques can make you more valuable to your employer.
• Advanced Education: Pursuing a master's degree or specialized certifications in data science or machine learning can open up higher-paying opportunities.
• Networking: Engage with industry professionals through conferences, workshops, and online platforms. Networking can lead to new job opportunities or promotions.
• Leadership Roles: Aim for leadership or managerial roles within your organization. These positions often come with higher salaries and additional responsibilities.
• Industry Shift: Consider moving to industries that pay higher salaries for data roles, such as finance, healthcare, or tech.

Educational Requirements

Most BI Analyst 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 is increasingly preferred, especially for roles that involve complex data analysis and machine learning tasks. Some positions may also require coursework in business analytics or specific programming languages like Python or R.

Helpful Certifications

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

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

These certifications can validate your skills in data analysis, machine learning, and cloud-based data solutions, making you a more competitive candidate.

Experience Requirements

Typically, a BI Analyst in AI/ML/Data Science is expected to have 3-5 years of experience in data analysis or a related field. Experience with data visualization tools (such as Tableau or Power BI), programming languages (like Python or SQL), and machine learning frameworks (such as TensorFlow or PyTorch) is often required. Experience in a specific industry can also be beneficial, as it provides context for data-driven decision-making.

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