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

Salary details

The average mid-level / intermediate Data Specialist salary lies between USD 60,000 and USD 88,000 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. 17, 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, Data management and Data quality. 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:

Excel | 236 jobs Data management | 179 jobs Data quality | 174 jobs Research | 146 jobs SQL | 108 jobs Privacy | 107 jobs Data analysis | 102 jobs Engineering | 100 jobs Testing | 97 jobs Finance | 93 jobs Security | 83 jobs Power BI | 79 jobs Data visualization | 73 jobs GCP | 56 jobs Pharma | 56 jobs Python | 54 jobs SAS | 54 jobs Data governance | 54 jobs Tableau | 49 jobs Statistics | 46 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 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 | 223 jobs Health care | 155 jobs Flex hours | 142 jobs Competitive pay | 91 jobs Team events | 85 jobs Startup environment | 78 jobs Equity / stock options | 69 jobs Flex vacation | 68 jobs Insurance | 67 jobs Salary bonus | 54 jobs Medical leave | 44 jobs Parental leave | 42 jobs Wellness | 40 jobs 401(k) matching | 26 jobs Relocation support | 16 jobs Home office stipend | 14 jobs Gear | 12 jobs Transparency | 12 jobs Conferences | 12 jobs Flexible spending account | 8 jobs

Salary Composition

In the United States, the salary composition for a Mid-level/Intermediate Data Specialist in AI/ML/Data Science can vary significantly based on region, industry, and company size. Typically, the salary is composed of a fixed base salary, which forms the bulk of the compensation package. This base salary can range from 70% to 90% of the total compensation. Bonuses, which can be performance-based or company-wide, often account for 5% to 15% of the total salary. Additional remuneration may include stock options, especially in tech companies, and other benefits such as health insurance, retirement contributions, and professional development allowances.

Regionally, salaries tend to be higher in tech hubs like San Francisco, New York, and Seattle due to the higher cost of living and competitive job markets. Industry-wise, tech companies, finance, and healthcare often offer higher salaries compared to education or non-profit sectors. Larger companies may provide more comprehensive benefits and bonuses, while smaller companies might offer equity or stock options as part of the compensation package.

Increasing Salary

To increase your salary from a Mid-level/Intermediate position, consider the following strategies:

• Skill Enhancement: Continuously update and expand your technical skills, particularly in high-demand areas like machine learning, deep learning, and big data technologies. Proficiency in programming languages such as Python, R, and SQL is crucial.

• Advanced Education: Pursuing a master's degree or specialized certifications can make you more competitive and open up higher-paying opportunities.

• Networking: Engage with professional networks and communities in AI/ML/Data Science. This can lead to new job opportunities and insights into industry trends.

• Leadership and Management Skills: Developing skills in project management and leadership can position you for roles with greater responsibility and higher pay.

• Industry Transition: Consider moving to industries that pay higher salaries for data specialists, such as finance or tech.

Educational Requirements

Most mid-level data specialist roles require at least a bachelor's degree in a related field such as Computer Science, Statistics, Mathematics, or Engineering. However, a master's degree in Data Science, Machine Learning, or a related discipline is increasingly preferred and can significantly enhance your job prospects and salary potential.

Helpful Certifications

Certifications can bolster your credentials and demonstrate expertise in specific areas. Some valuable certifications include:

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

These certifications can help validate your skills and make you stand out in the job market.

Experience Requirements

Typically, a mid-level data specialist role requires 3 to 5 years of relevant experience. This experience should include hands-on work with data analysis, machine learning models, and data visualization tools. Experience in managing projects and collaborating with cross-functional teams is also highly valued.

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