Salary for Mid-level / Intermediate BI Analyst during 2023

Salary details

The average mid-level / intermediate 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: Oct. 28, 2024

Salary trend

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

The three most common job tag items assiciated with mid-level / intermediate BI Analyst job listings are SQL, Power BI and Engineering. 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 | 17 jobs Power BI | 15 jobs Engineering | 12 jobs Tableau | 11 jobs Business Intelligence | 11 jobs Data analysis | 11 jobs Research | 10 jobs Data visualization | 10 jobs Finance | 9 jobs Python | 7 jobs ETL | 6 jobs Excel | 6 jobs Data Warehousing | 5 jobs Azure | 5 jobs Statistics | 5 jobs Mathematics | 5 jobs Computer Science | 5 jobs R | 4 jobs Economics | 4 jobs Consulting | 4 jobs

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

The three most common job benefits and perks assiciated with mid-level / intermediate 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 | 15 jobs Startup environment | 10 jobs Health care | 9 jobs Competitive pay | 9 jobs Team events | 7 jobs Flex hours | 5 jobs Parental leave | 4 jobs Flex vacation | 4 jobs Salary bonus | 4 jobs Conferences | 3 jobs Insurance | 3 jobs Medical leave | 2 jobs Flexible spending account | 2 jobs 401(k) matching | 1 jobs Equity / stock options | 1 jobs Fitness / gym | 1 jobs Transparency | 1 jobs Snacks / Drinks | 1 jobs Home office stipend | 1 jobs Fertility benefits | 1 jobs

Salary Composition

The salary composition for a Mid-level/Intermediate BI Analyst in AI/ML/Data Science can vary significantly based on 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 tech hubs like Silicon Valley or New York, the base salary might be higher due to the cost of living and competitive market. In contrast, regions with a lower cost of living might offer a smaller base salary but compensate with bonuses or stock options. Industries such as finance or healthcare may offer higher bonuses due to the critical nature of data insights in these fields. Larger companies often provide more comprehensive benefits packages, including health insurance, retirement plans, and professional development opportunities, which can add significant value to the overall compensation package.

Increasing Salary

To increase your salary from this position, consider pursuing advanced roles such as Senior Data Scientist, AI Specialist, or Data Science Manager. These roles typically require a deeper understanding of machine learning algorithms, leadership skills, and the ability to drive strategic data initiatives. Gaining expertise in high-demand areas like deep learning, natural language processing, or big data analytics can also make you more valuable. Networking within the industry, attending conferences, and contributing to open-source projects can enhance your visibility and open up opportunities for higher-paying roles. Additionally, negotiating your salary during performance reviews or when switching jobs can lead to significant increases.

Educational Requirements

Most mid-level BI Analyst positions in AI/ML/Data Science require at least a bachelor's degree in a related field such as Computer Science, Statistics, Mathematics, or Engineering. However, a master's degree or Ph.D. can be advantageous and is often preferred by employers, especially for roles that involve complex data modeling and machine learning tasks. Continuous learning through online courses, workshops, and bootcamps can also help you stay updated with the latest technologies and methodologies in the field.

Helpful Certifications

Certifications can bolster 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
• TensorFlow Developer Certificate

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

Required Experience

Typically, a mid-level BI Analyst role requires 3-5 years of experience in data analysis, business intelligence, or a related field. Experience with data visualization tools like Tableau or Power BI, proficiency in SQL, and familiarity with programming languages such as Python or R are often expected. Experience in applying machine learning models and working with large datasets can also be crucial, especially in tech-driven industries.

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