Salary for Mid-level / Intermediate Data Specialist in United States during 2023

Salary details

The average mid-level / intermediate Data Specialist salary lies between USD 70,000 and USD 109,000 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: Dec. 15, 2024

Salary trend

Top 20 Job Tags for Mid-level / Intermediate Data Specialist roles

The three most common job tag items assiciated with mid-level / intermediate Data Specialist job listings are Excel, SQL and Data management. Below you find a list of the 20 most occuring job tags in 2023 and the number of open jobs that where associated with them during that period:

Excel | 17 jobs SQL | 15 jobs Data management | 14 jobs Engineering | 13 jobs Research | 11 jobs Statistics | 10 jobs Finance | 9 jobs Testing | 9 jobs Computer Science | 9 jobs Data analysis | 8 jobs Python | 7 jobs Data Analytics | 7 jobs Architecture | 7 jobs Data quality | 7 jobs R | 6 jobs Security | 6 jobs Consulting | 5 jobs Power BI | 5 jobs Jira | 5 jobs Privacy | 5 jobs

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

The three most common job benefits and perks assiciated with mid-level / intermediate Data Specialist job listings are Career development, Health care and Startup environment. Below you find a list of the 20 most occuring job perks or benefits in 2023 and the number of open jobs that where offering them during that period:

Career development | 26 jobs Health care | 21 jobs Startup environment | 15 jobs Flex hours | 11 jobs Competitive pay | 11 jobs Team events | 11 jobs Flex vacation | 10 jobs 401(k) matching | 7 jobs Equity / stock options | 7 jobs Salary bonus | 7 jobs Parental leave | 6 jobs Insurance | 4 jobs Wellness | 2 jobs Conferences | 2 jobs Medical leave | 2 jobs Unlimited paid time off | 2 jobs Gear | 1 jobs Home office stipend | 1 jobs

Salary Composition

The salary for a Mid-level/Intermediate Data Specialist in the AI/ML/Data Science field typically comprises a base salary, bonuses, and additional remuneration such as stock options or benefits. The base salary is the fixed component and usually forms the bulk of the total compensation package. Bonuses can vary significantly depending on the company's performance, individual performance, and industry standards. In tech-heavy regions like Silicon Valley, bonuses and stock options might be more prevalent, whereas in other regions, the base salary might be more emphasized. Larger companies often offer more comprehensive benefits packages, including health insurance, retirement plans, and sometimes educational stipends, which can add significant value to the overall compensation.

Steps to Increase Salary

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

• Skill Enhancement: Continuously update your skills in the latest AI/ML technologies and tools. Specializing in high-demand areas like deep learning, natural language processing, or data engineering can make you more valuable.
• Advanced Education: Pursuing a master's degree or even a Ph.D. in a relevant field can open up higher-paying opportunities.
• Networking: Engage with professional networks and communities. Attending conferences and meetups can lead to new job opportunities and insights into industry trends.
• Leadership Roles: Aim for roles that offer leadership responsibilities, such as team lead or project manager, which often come with higher pay.
• Industry Shift: Consider moving to industries that pay more for data specialists, such as finance, healthcare, or tech.

Educational Requirements

Most mid-level data specialist roles require at least a bachelor's degree in a relevant field such as computer science, statistics, mathematics, or engineering. However, many employers prefer candidates with a master's degree in data science, machine learning, or a related discipline. A strong foundation in programming, statistics, and data analysis is essential.

Helpful Certifications

Certifications can enhance your resume and demonstrate your expertise to potential employers. Some valuable certifications include:

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

These certifications can validate your skills in specific tools and platforms, making you more competitive in the job market.

Required Experience

Typically, a mid-level data specialist is expected to have 3-5 years of experience in data analysis, machine learning, or a related field. Experience with data visualization tools, programming languages like Python or R, and familiarity with machine learning frameworks such as TensorFlow or PyTorch is often required. Practical experience in handling large datasets and deploying machine learning models in production environments is highly valued.

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