Salary for Entry-level / Junior Data Analyst in United States during 2023

Salary details

The average entry-level / junior Data Analyst salary lies between USD 60,000 and USD 100,000 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 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 in the United States typically consists of a base salary, which is the fixed amount, and may include additional components such as bonuses and other forms of remuneration. The base salary is often the largest portion and is influenced by factors such as geographic location, industry, and company size. For instance, data analysts in tech hubs like San Francisco or New York may receive higher base salaries compared to those in smaller cities. Bonuses can vary significantly and are often tied to individual performance, company performance, or both. In larger companies, especially in the tech or finance sectors, bonuses can be a substantial part of the total compensation package. Additional remuneration might include stock options, especially in tech startups, or other benefits like health insurance, retirement contributions, and professional development allowances.

Steps to Increase Salary

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

• Skill Enhancement: Continuously upgrade your skills by learning advanced data analysis techniques, programming languages like Python or R, and tools such as SQL, Tableau, or Power BI.
• Specialization: Focus on a niche area within data analysis, such as machine learning, big data, or business intelligence, which can make you more valuable to employers.
• Networking: Build a strong professional network by attending industry conferences, joining relevant online communities, and connecting with peers and mentors.
• Advanced Education: Pursue further education, such as a master's degree in data science or a related field, which can open up higher-paying opportunities.
• Performance Excellence: Consistently demonstrate high performance and take on additional responsibilities to position yourself for 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 proficiency in data analysis tools and programming languages.

Helpful Certifications

While not always required, certain certifications can enhance your resume and demonstrate your commitment to the field. Some valuable certifications include:

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

These certifications can provide you with a structured learning path and validate your skills to potential employers.

Experience Requirements

For entry-level positions, employers typically look for candidates with some practical experience, which can be gained through internships, co-op programs, or relevant projects during your studies. Experience with data analysis tools, programming languages, and real-world data sets is highly valued. Demonstrating your ability to solve problems and communicate insights effectively is crucial.

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