Data Analyst Salary in United States during 2023

Salary details

The average Data Analyst salary lies between USD 81,900 and USD 138,240 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: Nov. 24, 2024

Salary trend

Top 20 Job Tags for Data Analyst roles

The three most common job tag items assiciated with Data Analyst job listings are SQL, Python and Tableau. 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 | 3888 jobs Python | 2788 jobs Tableau | 2263 jobs Statistics | 2193 jobs Data analysis | 2095 jobs Excel | 1956 jobs Engineering | 1771 jobs Power BI | 1732 jobs R | 1469 jobs Mathematics | 1350 jobs Data Analytics | 1309 jobs Data visualization | 1264 jobs Computer Science | 1255 jobs Research | 1138 jobs Finance | 1100 jobs Business Intelligence | 977 jobs Looker | 863 jobs KPIs | 844 jobs Testing | 843 jobs Machine Learning | 825 jobs

Top 20 Job Perks/Benefits for Data Analyst roles

The three most common job benefits and perks assiciated with 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 | 2882 jobs Health care | 1761 jobs Flex hours | 1418 jobs Startup environment | 1378 jobs Team events | 1086 jobs Competitive pay | 1071 jobs Flex vacation | 1024 jobs Equity / stock options | 913 jobs Insurance | 845 jobs Salary bonus | 824 jobs Parental leave | 744 jobs Medical leave | 536 jobs 401(k) matching | 456 jobs Wellness | 390 jobs Home office stipend | 300 jobs Fitness / gym | 295 jobs Gear | 262 jobs Unlimited paid time off | 228 jobs Relocation support | 157 jobs Yoga | 128 jobs

Salary Composition

In the United States, the salary composition for a Data Analyst in AI/ML/Data Science typically includes a base salary, bonuses, and additional remuneration such as stock options or benefits. The base salary is the fixed component and usually constitutes the majority of the total compensation package. Bonuses can vary significantly depending on the company’s performance, individual performance, and industry standards. For instance, tech companies and startups might offer stock options or equity as part of the compensation package, which can be a significant portion of the total remuneration, especially in high-growth companies.

Regional differences also play a role; for example, salaries in tech hubs like San Francisco or New York City tend to be higher due to the cost of living and competitive job market. In contrast, salaries might be lower in regions with a lower cost of living. Company size can also influence salary composition, with larger companies often providing more comprehensive benefits and bonuses compared to smaller firms.

Increasing Salary

To increase your salary from a Data Analyst position, consider the following steps:

• Skill Enhancement: Acquire advanced skills in machine learning, data engineering, or data science. Proficiency in programming languages like Python or R, and tools like TensorFlow or PyTorch, can make you more valuable.
• Advanced Education: Pursuing a master's degree or specialized certifications in data science or AI can open up higher-paying roles.
• Networking: Engage with industry professionals through conferences, workshops, and online platforms like LinkedIn to learn about new opportunities.
• Performance and Negotiation: Consistently exceed performance expectations and be prepared to negotiate your salary during performance reviews or when offered a new position.

Educational Requirements

Most Data Analyst roles 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 can be advantageous and is often preferred for more advanced positions. Some roles may also require coursework or experience in machine learning, data mining, or big data technologies.

Helpful Certifications

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

• Certified Analytics Professional (CAP)
• Google Data Analytics Professional Certificate
• Microsoft Certified: Azure Data Scientist Associate
• IBM Data Science Professional Certificate
• AWS Certified Machine Learning – Specialty

These certifications can help you stand out in the job market and may lead to higher salary offers.

Experience Requirements

Typically, entry-level Data Analyst positions require 1-3 years of experience in data analysis or a related field. For more advanced roles, 3-5 years of experience is often necessary. Experience with data visualization tools (e.g., Tableau, Power BI), statistical analysis, and database management (e.g., SQL) is commonly required. Experience in a specific industry, such as finance or healthcare, can also be beneficial.

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