Salary for Entry-level / Junior Data Analyst during 2023

Salary details

The average entry-level / junior Data Analyst salary lies between USD 53,800 and USD 92,700 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 Entry-level / Junior Data Analyst roles

The three most common job tag items assiciated with entry-level / junior Data Analyst job listings are SQL, Python and Excel. 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 | 927 jobs Python | 681 jobs Excel | 664 jobs Power BI | 515 jobs Tableau | 483 jobs Data analysis | 481 jobs Statistics | 479 jobs Engineering | 390 jobs Mathematics | 339 jobs R | 335 jobs Research | 307 jobs Computer Science | 304 jobs Data Analytics | 297 jobs Finance | 269 jobs Data visualization | 257 jobs Business Intelligence | 217 jobs Data quality | 211 jobs Testing | 197 jobs Agile | 189 jobs KPIs | 182 jobs

Top 20 Job Perks/Benefits for Entry-level / Junior Data Analyst roles

The three most common job benefits and perks assiciated with entry-level / junior Data Analyst job listings are Career development, Flex hours 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 | 743 jobs Flex hours | 372 jobs Health care | 338 jobs Startup environment | 323 jobs Team events | 314 jobs Flex vacation | 220 jobs Competitive pay | 213 jobs Insurance | 184 jobs Salary bonus | 177 jobs Equity / stock options | 148 jobs Parental leave | 133 jobs Medical leave | 80 jobs 401(k) matching | 67 jobs Yoga | 66 jobs Wellness | 63 jobs Relocation support | 53 jobs Fitness / gym | 50 jobs Home office stipend | 43 jobs Lunch / meals | 36 jobs Gear | 36 jobs

Salary Composition

The salary for an entry-level or junior data analyst typically consists of a fixed base salary, which forms the bulk of the compensation package. In the United States, this base salary can vary significantly depending on the region, industry, and company size. For instance, tech hubs like San Francisco or New York may offer higher base salaries compared to smaller cities. In addition to the base salary, some companies offer performance-based bonuses, which can range from 5% to 15% of the base salary. Larger companies or those in competitive industries might also provide stock options or equity as part of the compensation package, although this is less common for entry-level positions.

Increasing Salary

To increase your salary from an entry-level position, consider the following steps:

• Skill Development: Continuously improve your technical skills, such as proficiency in programming languages like Python or R, and data visualization tools like Tableau or Power BI.
• Advanced Education: Pursuing a master's degree in data science, statistics, or a related field can make you more competitive for higher-paying roles.
• Networking: Build a professional network by attending industry conferences, joining relevant online communities, and connecting with professionals on LinkedIn.
• Certifications: Obtain relevant certifications to demonstrate your expertise and commitment to the field.
• Experience: Gain experience by working on diverse projects, which can lead to promotions and salary increases.

Educational Requirements

Most entry-level data analyst positions require at least a bachelor's degree in a related field such as data science, statistics, computer science, mathematics, or economics. Some employers may accept candidates with degrees in other fields if they have relevant skills and experience. A strong foundation in mathematics and statistics is often essential, as is familiarity with data analysis tools and programming languages.

Helpful Certifications

While not always required, certain certifications can enhance your resume and demonstrate your expertise to potential employers. Some popular certifications include:

• Microsoft Certified: Data Analyst Associate
• Google Data Analytics Professional Certificate
• IBM Data Science Professional Certificate
• SAS Certified Data Scientist
• Certified Analytics Professional (CAP)

These certifications can help you stand out in a competitive job market and may lead to better job opportunities and higher salaries.

Required Experience

For entry-level positions, employers typically look for candidates with some practical experience, which can be gained through internships, co-op programs, or relevant coursework. Experience with data analysis tools, programming languages, and data visualization is often expected. While specific experience requirements can vary, demonstrating your ability to work with data and solve real-world problems is crucial.

Related salaries

Want to contribute?