Data scientist is one of the most sought-after titles in tech today. But, not everyone can agree on what a data scientist actually does, or what skills are needed. This lack of agreement is partly due to the fact that there isn’t just one type of data scientist, or one skillset needed, according to a new report from job search site Glassdoor.

Glassdoor extracted a sample of 10,000 data scientist job listings posted on the site this year, and examined the estimated median base pay by job to better understand the market value of different kinds of data science skills.

Python, R, and SQL were the top three skills found in data science job listings, Glassdoor found. Using a clustering algorithm, the company grouped job descriptions into specific types of jobs, based on the actual skills listed by employers, as well as the average estimated pay for each type.

SEE: Job description: Data scientist (Tech Pro Research)

Here are the three main types of data science jobs available, the skills necessary, the percentage of data science jobs they make up, and the average estimated salary.

1. Core data scientist

Skills likely to have: Python, R, SQL

Percentage of data science jobs: 71%

Average estimated salary: $116,203

Companies currently hiring for these roles: Google,Aetna,Microsoft

2. Researcher

Skills likely to have: SAS, Matlab, Java, Hadoop, Python, R

Percentage of data science jobs: 15%

Average estimated salary: $112,346

Companies currently hiring for these roles: KPMG,Bank of America,Allstate

3. Big data specialist

Skills likely to have: Spark, Hive, Hadoop, Java, Python

Percentage of data science jobs: 14%

Average estimated salary: $121,246

Companies currently hiring for these roles: Experian,Amazon,Zillow

Big data specialists are paid most due to supply and demand, Pablo Ruiz Junco, Glassdoor economic research fellow, told TechRepublic. “As the size of data at companies grow larger and larger, there is higher demand for employees with specific skills who can effectively organize and analyze this data,” he said. “At the same time, the amount of people with these skills is still relatively low compared to the demand, which results in higher pay.”

Clearly, the skills that individual data scientists bring to the table can have a large impact on pay. Job seekers should consider what role they are most interested in, and make a cost-benefit analysis of which skills are worth spending time learning, the report noted.

Employers seeking data scientists can use this information to determine the types of skills required to meet their individual business needs, and to calculate how much they should expect to pay these professionals according to market rates, Ruiz Junco said. “Having this information at hand can help them fill positions more quickly and efficiently, and help them truly understand what kind of data scientist they need,” he added.