Salary for Entry-level / Junior Analyst in United States during 2024

Salary details

The average entry-level / junior Analyst salary lies between USD 72,862 and USD 120,452 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: Jan. 26, 2025

Salary trend

Top 20 Job Tags for Entry-level / Junior Analyst roles

The three most common job tag items assiciated with entry-level / junior Analyst job listings are SQL, Python and Excel. 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 | 8041 jobs Python | 6691 jobs Excel | 5503 jobs Statistics | 5182 jobs Data analysis | 5130 jobs Power BI | 4757 jobs Engineering | 4172 jobs Tableau | 4164 jobs Research | 3588 jobs R | 3446 jobs Computer Science | 3434 jobs Data Analytics | 3089 jobs Finance | 2861 jobs Mathematics | 2709 jobs Data visualization | 2611 jobs Data quality | 2428 jobs Data management | 2377 jobs Testing | 2302 jobs Business Intelligence | 2217 jobs Machine Learning | 2145 jobs

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

The three most common job benefits and perks assiciated with entry-level / junior 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 | 7363 jobs Health care | 4317 jobs Flex hours | 3558 jobs Competitive pay | 2471 jobs Team events | 2311 jobs Equity / stock options | 2186 jobs Startup environment | 2131 jobs Insurance | 2009 jobs Flex vacation | 1871 jobs Salary bonus | 1700 jobs Parental leave | 1384 jobs Medical leave | 1378 jobs Wellness | 1203 jobs 401(k) matching | 840 jobs Fitness / gym | 388 jobs Relocation support | 362 jobs Transparency | 331 jobs Home office stipend | 307 jobs Flexible spending account | 299 jobs Gear | 273 jobs

Salary Composition

In the United States, the salary for an entry-level or junior analyst position in AI/ML/Data Science typically consists of a base salary, performance bonuses, and sometimes additional remuneration such as stock options or profit-sharing. The base salary is the fixed component and usually makes up the majority of the total compensation package. Performance bonuses can vary significantly depending on the company’s policy and your individual performance. Additional remuneration like stock options is more common in tech companies, especially startups, and can be a significant part of the compensation in larger tech hubs like Silicon Valley. The composition can also vary by region, with higher base salaries often found in areas with a higher cost of living, such as New York City or San Francisco. Industry also plays a role; for instance, tech companies might offer more in stock options, while finance companies might offer higher cash bonuses.

Increasing Salary

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

• Skill Enhancement: Continuously upgrade your skills by learning new programming languages, tools, or methodologies relevant to AI/ML/Data Science.
• Advanced Education: Pursuing a master's degree or specialized certifications can make you more competitive.
• Networking: Build a strong professional network by attending industry conferences, meetups, and online forums.
• Performance Excellence: Consistently exceed performance expectations to position yourself for promotions and raises.
• Industry Switch: Consider moving to industries that pay higher salaries for data science roles, such as finance or healthcare.

Educational Requirements

Most entry-level positions in AI/ML/Data Science require at least a bachelor's degree in a related field such as computer science, statistics, mathematics, or engineering. Some roles may accept degrees in other fields if you have relevant coursework or experience in data analysis or programming. A strong foundation in statistics, mathematics, and programming is essential. Increasingly, employers are looking for candidates with a master's degree, especially for roles that require more specialized knowledge.

Helpful Certifications

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

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

These certifications can help validate your skills and knowledge in specific tools and platforms used in the industry.

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. Experience with data analysis, machine learning models, and programming languages like Python or R is often expected. Familiarity with data visualization tools and cloud platforms can also be beneficial. While extensive professional experience is not required, demonstrating hands-on experience through projects or internships can set you apart.

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