Salary for Mid-level / Intermediate Analyst in United States during 2024

Salary details

The average mid-level / intermediate Analyst salary lies between USD 80,000 and USD 137,000 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: Feb. 23, 2025

Salary trend

Top 20 Job Tags for Mid-level / Intermediate Analyst roles

The three most common job tag items assiciated with mid-level / intermediate Analyst job listings are SQL, Python and Data analysis. 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 | 2791 jobs Python | 2198 jobs Data analysis | 1865 jobs Statistics | 1839 jobs Excel | 1683 jobs Tableau | 1554 jobs Engineering | 1478 jobs Power BI | 1428 jobs Computer Science | 1225 jobs R | 1108 jobs Research | 1104 jobs Data visualization | 1068 jobs Data Analytics | 1024 jobs Finance | 1009 jobs Mathematics | 1003 jobs Data quality | 814 jobs Business Intelligence | 757 jobs Testing | 751 jobs Machine Learning | 730 jobs Data management | 698 jobs

Top 20 Job Perks/Benefits for Mid-level / Intermediate Analyst roles

The three most common job benefits and perks assiciated with mid-level / intermediate 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 | 2329 jobs Health care | 1571 jobs Flex hours | 1069 jobs Competitive pay | 946 jobs Equity / stock options | 751 jobs Startup environment | 743 jobs Insurance | 715 jobs Team events | 679 jobs Flex vacation | 656 jobs Salary bonus | 590 jobs Parental leave | 550 jobs Medical leave | 531 jobs Wellness | 490 jobs 401(k) matching | 405 jobs Transparency | 155 jobs Fitness / gym | 139 jobs Home office stipend | 134 jobs Gear | 122 jobs Unlimited paid time off | 121 jobs Relocation support | 118 jobs

Salary Composition

In the United States, the salary composition for a mid-level/intermediate AI/ML/Data Science Analyst typically includes a combination of a fixed base salary, performance-based bonuses, and additional remuneration such as stock options or equity, especially in tech companies. The base salary often constitutes the majority of the total compensation package, ranging from 70% to 85%. Bonuses can vary significantly depending on the company and industry, typically ranging from 10% to 20% of the base salary. Additional remuneration, such as stock options, is more common in larger tech companies or startups and can add another 5% to 15% to the total compensation. Regional differences also play a role; for instance, salaries in tech hubs like San Francisco or New York City tend to be higher due to the cost of living and competitive job markets.

Steps to Increase Salary

To increase your salary from a mid-level position, consider the following strategies:

• Skill Enhancement: Continuously update and expand your technical skills, particularly in emerging areas like deep learning, natural language processing, or big data technologies.
• Advanced Education: Pursuing a master's degree or a Ph.D. in a relevant field can open up higher-paying opportunities.
• Leadership Roles: Aim for roles that involve team leadership or project management, as these often come with higher pay.
• Industry Transition: Consider moving to industries that pay higher salaries for data science roles, such as finance, healthcare, or tech.
• Networking and Visibility: Attend industry conferences, contribute to open-source projects, or publish research to increase your visibility and network within the industry.

Educational Requirements

Most mid-level AI/ML/Data Science Analyst positions require at least a bachelor's degree in a relevant field such as computer science, statistics, mathematics, or engineering. However, a master's degree is increasingly preferred and can be a significant advantage. Degrees that offer a strong foundation in programming, statistical analysis, and machine learning are particularly valued.

Helpful Certifications

While not always required, certain certifications can enhance your resume and demonstrate your expertise:

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

These certifications can validate your skills in specific tools and platforms, making you more attractive to potential employers.

Required Experience

Typically, a mid-level position requires 3 to 5 years of relevant experience in data science or a related field. This experience should include hands-on work with data analysis, machine learning model development, and proficiency in programming languages such as Python or R. Experience with data visualization tools and cloud platforms is also beneficial.

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