Analyst Salary in United States during 2024

Salary details

The average Analyst salary lies between USD 82,000 and USD 142,500 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: Dec. 22, 2024

Top 20 Job Tags for Analyst roles

The three most common job tag items assiciated with Analyst job listings are SQL, Python and Statistics. 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 | 16933 jobs Python | 13987 jobs Statistics | 11204 jobs Data analysis | 10489 jobs Excel | 10091 jobs Tableau | 9431 jobs Engineering | 9062 jobs Power BI | 8802 jobs R | 7159 jobs Research | 7052 jobs Computer Science | 6984 jobs Data Analytics | 6444 jobs Finance | 6203 jobs Mathematics | 5887 jobs Data visualization | 5834 jobs Testing | 5190 jobs Data quality | 5078 jobs Business Intelligence | 4750 jobs Machine Learning | 4660 jobs Data management | 4577 jobs

Top 20 Job Perks/Benefits for Analyst roles

The three most common job benefits and perks assiciated with 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 | 14853 jobs Health care | 9456 jobs Flex hours | 6869 jobs Competitive pay | 5675 jobs Equity / stock options | 4799 jobs Team events | 4642 jobs Startup environment | 4634 jobs Insurance | 4391 jobs Flex vacation | 3968 jobs Salary bonus | 3570 jobs Medical leave | 3324 jobs Parental leave | 3254 jobs Wellness | 2830 jobs 401(k) matching | 2124 jobs Transparency | 935 jobs Fitness / gym | 850 jobs Home office stipend | 712 jobs Relocation support | 698 jobs Gear | 612 jobs Flexible spending account | 610 jobs

Salary Composition

In the United States, the salary composition for an AI/ML/Data Science Analyst can vary significantly based on region, industry, and company size. Typically, the salary is divided into a base salary, performance bonuses, and additional remuneration such as stock options or profit-sharing.

• Base Salary: This is the fixed component and usually constitutes the majority of the total compensation package. In tech hubs like San Francisco or New York, the base salary might be higher due to the cost of living and competitive job market.

• Bonuses: Performance bonuses are common and can range from 10% to 20% of the base salary, depending on individual and company performance. Industries like finance or tech often offer higher bonuses compared to others.

• Additional Remuneration: This can include stock options, especially in tech startups, or profit-sharing plans in larger corporations. Benefits such as health insurance, retirement plans, and paid time off also contribute to the overall compensation package.

Increasing Salary

To increase your salary from the position of an AI/ML/Data Science Analyst, consider the following steps:

• Skill Enhancement: Continuously update your skills with the latest tools and technologies in AI and data science. Specializing in high-demand areas like deep learning, natural language processing, or big data analytics can make you more valuable.

• Advanced Education: Pursuing a master's degree or a Ph.D. in a relevant field can open up higher-paying opportunities and leadership roles.

• Networking: Build a strong professional network by attending industry conferences, joining relevant online communities, and connecting with peers and mentors. Networking can lead to new job opportunities and salary negotiations.

• Performance and Negotiation: Consistently demonstrate high performance and take on challenging projects. When the time is right, negotiate for a raise based on your contributions and market research.

Educational Requirements

Most AI/ML/Data Science Analyst positions require at least a bachelor's degree in a related field such as computer science, data science, statistics, or mathematics. However, many employers prefer candidates with a master's degree or higher, especially for more advanced roles. Coursework in machine learning, data mining, and statistical analysis is often essential.

Helpful Certifications

While not always mandatory, certain certifications can enhance your credentials and demonstrate your expertise:

• Certified Analytics Professional (CAP): This certification is recognized across industries and validates your ability to transform data into valuable insights.

• Google Professional Machine Learning Engineer: This certification demonstrates your proficiency in designing, building, and deploying machine learning models on Google Cloud.

• AWS Certified Machine Learning – Specialty: This is ideal for those working with AWS services and looking to validate their skills in building, training, and deploying ML models.

Experience Requirements

Typically, employers look for candidates with 2-5 years of experience in data analysis, machine learning, or a related field. Experience with programming languages like Python or R, data visualization tools, and machine learning frameworks is often required. Internships, co-op programs, or relevant project work during your studies can also count towards this experience.

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