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 147,000 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. 10, 2024

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 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 | 2341 jobs Python | 1832 jobs Statistics | 1549 jobs Data analysis | 1539 jobs Excel | 1397 jobs Tableau | 1322 jobs Engineering | 1244 jobs Power BI | 1183 jobs Computer Science | 1032 jobs Research | 967 jobs R | 926 jobs Data visualization | 899 jobs Data Analytics | 860 jobs Mathematics | 851 jobs Finance | 838 jobs Data quality | 680 jobs Business Intelligence | 666 jobs Testing | 628 jobs Machine Learning | 608 jobs Economics | 584 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 | 1951 jobs Health care | 1328 jobs Flex hours | 888 jobs Competitive pay | 789 jobs Equity / stock options | 646 jobs Startup environment | 624 jobs Insurance | 607 jobs Team events | 584 jobs Flex vacation | 552 jobs Salary bonus | 510 jobs Parental leave | 473 jobs Medical leave | 471 jobs Wellness | 421 jobs 401(k) matching | 351 jobs Transparency | 126 jobs Home office stipend | 121 jobs Fitness / gym | 118 jobs Unlimited paid time off | 113 jobs Relocation support | 104 jobs Gear | 102 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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