Data Specialist Salary in 2022
💰 The median Data Specialist Salary in 2022 is USD 110,000
✏️ This salary info is based on 11 individual salaries reported during 2022
Salary details
The average Data Specialist salary lies between USD 70,000 and USD 148,700 globally. 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.
- Job title
- Data Specialist
- Experience
- all levels
- Region
- global/worldwide
- Salary year
- 2022
- Sample size
- 11
- Top 10%
-
- Top 25%
-
- Median
-
- Bottom 25%
-
- Bottom 10%
-
All data shown are full-time equivalent (FTE) salaries. Part-time salary information has been extrapolated to its FTE value.
Last updated:Salary trend
Top 20 Job Tags for Data Specialist roles
The three most common job tag items assiciated with Data Specialist job listings are SQL, Excel and Research. Below you find a list of the 20 most occuring job tags in 2022 and the number of open jobs that where associated with them during that period:
SQL | 55 jobs Excel | 47 jobs Research | 44 jobs Engineering | 40 jobs Data analysis | 34 jobs Python | 31 jobs R | 28 jobs Computer Science | 24 jobs Finance | 23 jobs Data quality | 23 jobs Tableau | 21 jobs Data management | 21 jobs Testing | 19 jobs Security | 17 jobs Statistics | 16 jobs Mathematics | 16 jobs RDBMS | 16 jobs Machine Learning | 14 jobs R&D | 14 jobs MySQL | 12 jobsTop 20 Job Perks/Benefits for Data Specialist roles
The three most common job benefits and perks assiciated with Data Specialist job listings are Career development, Startup environment and Flex hours. Below you find a list of the 20 most occuring job perks or benefits in 2022 and the number of open jobs that where offering them during that period:
Career development | 64 jobs Startup environment | 60 jobs Flex hours | 52 jobs Team events | 47 jobs Flex vacation | 36 jobs Health care | 36 jobs Parental leave | 29 jobs Competitive pay | 20 jobs Equity / stock options | 18 jobs Wellness | 17 jobs 401(k) matching | 12 jobs Insurance | 12 jobs Medical leave | 11 jobs Snacks / Drinks | 10 jobs Salary bonus | 6 jobs Home office stipend | 6 jobs Unlimited paid time off | 6 jobs Fitness / gym | 5 jobs Transparency | 4 jobs Fertility benefits | 4 jobsSalary Composition
The salary composition for a Data Specialist in AI/ML/Data Science can vary significantly based on region, industry, and company size. Generally, the salary is composed of a fixed base salary, a performance-based bonus, and additional remuneration such as stock options or benefits. In tech hubs like Silicon Valley, the base salary might be higher, but the cost of living is also elevated. In contrast, regions with a lower cost of living might offer a smaller base salary but could compensate with a more substantial bonus or stock options. Industries such as finance or healthcare might offer higher bonuses due to the critical nature of data in these fields. Larger companies often provide more comprehensive benefits packages, including health insurance, retirement plans, and professional development opportunities, which can add significant value to the overall compensation package.
Increasing Salary
To increase your salary from a Data Specialist position, consider the following steps:
- Skill Enhancement: Continuously update your skills in the latest AI/ML technologies and tools. Specializing in a niche area can make you more valuable.
- Advanced Education: Pursuing a master's degree or Ph.D. in a related field can open doors to higher-paying roles.
- Networking: Engage with industry professionals through conferences, workshops, and online platforms to learn about new opportunities.
- Leadership Roles: Aim for positions that involve team leadership or project management, as these often come with higher pay.
- Switching Companies: Sometimes, moving to a different company can result in a significant salary increase, especially if the new company values your specific skill set more.
Educational Requirements
Most Data Specialist roles in AI/ML/Data Science require at least a bachelor's degree in a related field such as Computer Science, Statistics, Mathematics, or Engineering. However, many employers prefer candidates with a master's degree or higher, especially for more advanced positions. Coursework in machine learning, data mining, and statistical analysis is particularly beneficial.
Helpful Certifications
While not always required, certain certifications can enhance your resume and demonstrate your expertise:
- Certified Data Scientist (CDS)
- Google Professional Machine Learning Engineer
- Microsoft Certified: Azure Data Scientist Associate
- AWS Certified Machine Learning – Specialty
- TensorFlow Developer Certificate
These certifications can validate your skills and knowledge, making you a more attractive candidate to potential employers.
Experience Requirements
Typically, a Data Specialist role requires 2-5 years of experience in data analysis, machine learning, or a related field. Experience with data visualization tools, programming languages like Python or R, and machine learning frameworks is often necessary. Practical experience in handling large datasets and working on real-world projects is highly valued.
Related salaries
Want to contribute?
📝 Submit your salary info
Enter your own salary data for the current or past work year. It's quite simple and doesn't take more than a minute to fill out.
Go to salary survey📢 Share our salary survey
Share our "in-less-than-a-minute survey" with others working in the field of AI, ML, Data Science. The more data we have the better for everyone.
💾 Download the data
All collected information will be updated into a public dataset regularly and provided as a download free for anyone to use.
Go to download page🚀 Search for jobs & talent
If you're thinking about a career change or want to hire fresh talent quickly check out the jobs page.
Go to frontpageAbout this project
We collect salary information anonymously from professionals and employers all over the world and make it publicly available for anyone to use, share and play around with.
Our goal is to have open salary data for everyone. So newbies, experienced pros, hiring managers, recruiters and also startup founders or people wanting to switch careers can make better decisions.