Data Analyst Salary in 2024

Salary details

The average Data Analyst salary lies between USD 75,000 and USD 135,111 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 Data Analyst roles

The three most common job tag items assiciated with Data Analyst job listings are SQL, Python and Data analysis. 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 | 9395 jobs Python | 6846 jobs Data analysis | 6056 jobs Statistics | 5803 jobs Excel | 5574 jobs Tableau | 5381 jobs Power BI | 4965 jobs Engineering | 4574 jobs Data Analytics | 3787 jobs Computer Science | 3554 jobs R | 3532 jobs Research | 3362 jobs Data visualization | 3308 jobs Mathematics | 2935 jobs Finance | 2902 jobs Data quality | 2603 jobs Testing | 2482 jobs Business Intelligence | 2322 jobs Data management | 2239 jobs Security | 2049 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 2024 and the number of open jobs that where offering them during that period:

Career development | 7659 jobs Health care | 4992 jobs Flex hours | 3846 jobs Competitive pay | 2823 jobs Startup environment | 2613 jobs Team events | 2549 jobs Equity / stock options | 2504 jobs Insurance | 2278 jobs Flex vacation | 2195 jobs Salary bonus | 1964 jobs Parental leave | 1774 jobs Medical leave | 1698 jobs Wellness | 1394 jobs 401(k) matching | 1206 jobs Fitness / gym | 497 jobs Home office stipend | 456 jobs Transparency | 441 jobs Unlimited paid time off | 368 jobs Gear | 367 jobs Flexible spending account | 333 jobs

Salary Composition

The salary composition for a Data 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: base salary, bonuses, and additional remuneration such as stock options or benefits.

• Base Salary: This is the fixed annual amount and usually constitutes the largest portion of the total compensation. In regions with a high cost of living, such as the San Francisco Bay Area or New York City, base salaries tend to be higher to offset living expenses.

• Bonuses: These are performance-based and can vary widely. In tech-heavy industries or larger companies, bonuses might be more substantial, often tied to individual performance, team success, or company profitability.

• Additional Remuneration: This can include stock options, especially in startups or tech companies, as well as benefits like health insurance, retirement contributions, and other perks. Larger companies might offer more comprehensive benefits packages.

Increasing Salary

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

• Skill Enhancement: Continuously upgrade your skills in advanced analytics, machine learning, and data visualization tools. Proficiency in programming languages like Python or R, and experience with big data technologies, can make you more valuable.

• Specialization: Focus on a niche area within data science, such as natural language processing, computer vision, or deep learning. Specializing can make you a sought-after expert.

• Advanced Education: Pursuing a master's degree or Ph.D. in data science, computer science, or a related field can open doors to higher-paying roles.

• Networking and Professional Development: Attend industry conferences, join professional organizations, and engage in networking to learn about new opportunities and trends.

• Leadership Roles: Aim for positions with more responsibility, such as a team lead or manager, which typically come with higher pay.

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, many employers prefer candidates with a master's degree in data science or a related discipline, as it provides a deeper understanding of complex analytical techniques and tools.

Helpful Certifications

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

• Certified Analytics Professional (CAP): This certification covers a broad range of analytics topics and is recognized across industries.

• Google Data Analytics Professional Certificate: Offered through Coursera, this program provides a comprehensive introduction to data analytics.

• Microsoft Certified: Azure Data Scientist Associate: This certification is beneficial if you work with Microsoft's Azure platform.

• AWS Certified Data Analytics – Specialty: Ideal for those working with Amazon Web Services, focusing on data analytics.

Experience Requirements

Typically, employers look for candidates with 2-5 years of experience in data analysis or a related field. Experience with data manipulation, statistical analysis, and data visualization is crucial. Familiarity with machine learning models and big data technologies can also be advantageous.

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