Analyst Salary in United States during 2024

Salary details

The average Analyst salary lies between USD 85,000 and USD 146,200 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. 10, 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 | 14298 jobs Python | 11704 jobs Statistics | 9358 jobs Data analysis | 8674 jobs Excel | 8494 jobs Tableau | 7991 jobs Engineering | 7604 jobs Power BI | 7332 jobs Research | 6023 jobs R | 5965 jobs Computer Science | 5876 jobs Data Analytics | 5438 jobs Finance | 5143 jobs Mathematics | 4918 jobs Data visualization | 4833 jobs Testing | 4387 jobs Data quality | 4275 jobs Business Intelligence | 4164 jobs Machine Learning | 3918 jobs Data management | 3806 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 | 12506 jobs Health care | 7952 jobs Flex hours | 5840 jobs Competitive pay | 4781 jobs Equity / stock options | 4059 jobs Startup environment | 3991 jobs Team events | 3949 jobs Insurance | 3695 jobs Flex vacation | 3390 jobs Salary bonus | 3062 jobs Medical leave | 2805 jobs Parental leave | 2734 jobs Wellness | 2402 jobs 401(k) matching | 1830 jobs Transparency | 754 jobs Fitness / gym | 722 jobs Home office stipend | 617 jobs Relocation support | 593 jobs Gear | 525 jobs Flexible spending account | 513 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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