Salary for Mid-level / Intermediate Data Analyst during 2023

Salary details

The average mid-level / intermediate Data Analyst salary lies between USD 67,672 and USD 110,736 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. 24, 2024

Salary trend

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

The three most common job tag items assiciated with mid-level / intermediate Data Analyst job listings are SQL, Python and Data analysis. 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 | 662 jobs Python | 453 jobs Data analysis | 445 jobs Tableau | 409 jobs Statistics | 406 jobs Power BI | 337 jobs Excel | 335 jobs Engineering | 323 jobs Computer Science | 265 jobs Mathematics | 254 jobs Data Analytics | 226 jobs Research | 223 jobs Data visualization | 215 jobs R | 204 jobs Finance | 180 jobs Business Intelligence | 161 jobs Data quality | 151 jobs Machine Learning | 150 jobs Testing | 149 jobs Economics | 139 jobs

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

The three most common job benefits and perks assiciated with mid-level / intermediate Data Analyst 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 2023 and the number of open jobs that where offering them during that period:

Career development | 471 jobs Health care | 369 jobs Flex hours | 260 jobs Startup environment | 250 jobs Competitive pay | 230 jobs Team events | 183 jobs Flex vacation | 173 jobs Insurance | 153 jobs Parental leave | 134 jobs Salary bonus | 126 jobs Equity / stock options | 104 jobs Medical leave | 98 jobs 401(k) matching | 94 jobs Gear | 64 jobs Wellness | 57 jobs Fitness / gym | 50 jobs Home office stipend | 49 jobs Unlimited paid time off | 37 jobs Relocation support | 19 jobs Yoga | 17 jobs

Salary Composition

The salary for a Mid-level/Intermediate Data Analyst in AI/ML/Data Science typically comprises a fixed base salary, performance bonuses, and additional remuneration such as stock options or benefits. The base salary often constitutes the majority of the total compensation package, usually around 70-80%. Performance bonuses can vary significantly depending on the company and industry, ranging from 10-20% of the base salary. Additional remuneration, such as stock options, profit-sharing, or comprehensive benefits packages, can make up the remaining 5-10%.

Regional differences also play a significant role; for instance, salaries in tech hubs like San Francisco or New York may be higher due to the cost of living and demand for skilled professionals. Industry-wise, tech companies and financial services often offer more competitive compensation packages compared to non-tech sectors. Larger companies may provide more substantial bonuses and stock options, while smaller companies might offer more flexibility or unique benefits.

Next Steps for Salary Increase

To increase your salary from a Mid-level Data Analyst position, consider the following strategies:

• Skill Enhancement: Acquire advanced skills in machine learning, deep learning, or big data technologies. Proficiency in tools like TensorFlow, PyTorch, or Apache Spark can make you more valuable.
• Specialization: Focus on a niche area within data science, such as natural language processing, computer vision, or AI ethics, to differentiate yourself.
• Leadership Roles: Aim for roles with leadership responsibilities, such as a Senior Data Analyst or Data Science Manager, which typically offer higher salaries.
• Networking and Visibility: Attend industry conferences, contribute to open-source projects, or publish articles to increase your visibility and network within the industry.
• Further Education: Consider pursuing a master's degree or relevant certifications to enhance your qualifications and bargaining power.

Educational Requirements

Most Mid-level Data Analyst positions require at least a bachelor's degree in a related field such as Computer Science, Statistics, Mathematics, or Engineering. A strong foundation in these areas is crucial for understanding data analysis techniques and tools. Some employers may prefer candidates with a master's degree, especially for roles that involve more complex data modeling or machine learning tasks.

Helpful Certifications

Certifications can bolster your resume and demonstrate your commitment to professional development. Some valuable certifications include:

• Certified Analytics Professional (CAP): Recognized for its comprehensive coverage of analytics skills.
• Microsoft Certified: Azure Data Scientist Associate: Useful for those working with Azure's data science tools.
• Google Professional Data Engineer: Focuses on designing and building data processing systems.
• AWS Certified Machine Learning – Specialty: Ideal for those working with AWS services in machine learning.

Required Experience

Typically, a Mid-level Data Analyst role requires 3-5 years of experience in data analysis or a related field. This experience should include hands-on work with data manipulation, statistical analysis, and data visualization tools. Familiarity with programming languages such as Python or R, and experience with SQL for database querying, are often essential. Experience in a specific industry can also be beneficial, as it provides context and understanding of industry-specific data challenges.

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