Hiring data scientists might not have been as popular a decade ago, but it sure is now. Due to the rising importance of big data, data scientists became highly sought-after. In fact, their ability to solve complex problems and draw conclusions from the available data sets is essential for many businesses that are looking for new ways to turn a profit.
At the same time, trusting data scientists to make important decisions can be challenging for many businesses. That’s precisely why you should pick the right person carefully. As demand is increasing, though, it might soon become difficult to attract top talent. Since it’s often the subject of negotiation with candidates, you might want to become familiar with an average data scientist salary to make sure you land the best person for the job.
In general, the data scientist salary depends on several factors:
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- Experience
- Job title/position
- Nivel de antigüedad
- Industria
- Company size
- Location
- Education & additional skills
To give you an overview of the subject, we’ve put together a comparison based on data scientist average salary data across the US from PayScale, Glassdoor, ZipRecruiter, and Indeed. Let’s dive in.
Average data scientist salary
Según Escala salarial, the average data scientist salary in the US ranges from $68,000 to $135,00 with an average of $96,551 (at the time of the publication). The median hourly rate, on the other hand, amounts to $36.76.
Currency: USD | Updated: 13 Oct 2021 | Individuals Reporting: 7,549
The data scientist average salary reported by Glassdoor is $117,345 per year.
Currency: USD | Updated: Oct 12 2021 | Individuals Reporting: 18,354
The chart from ZipRecruiter clearly indicates that the upward trend continues, as the average annual pay for a data scientist equals $119,413 a year.
Currency: USD | Updated: 06 Oct 2021 | Individual data sources: –
The data collected by De hecho.com is slightly different than usual, though. The average salary that can be found on the platform tends to be the highest, but this time data scientists are said to earn “only” $80,263 a year on average. This number is also based on comparatively little salary data, in comparison with other sources.
As already mentioned, these differences stem from a number of factors: the source itself, as well as the experience of the candidates, their location or knowledge, and the skills required for the specific position. How exactly does each of these factors affect the data scientist average salary?
Experience: entry-level vs senior data scientist salary
It should come as no surprise that average pay changes with the level of experience. As reported by Escala salarial, an entry-level data scientist salary (with less than 1 year of experience) equals $85,096 on average. Data scientists with 1-4 years of experience, on the other hand, can expect an average total compensation of $95,067, while 5-9 years of experience means earning $109,743 on average. The average senior data scientist salary, though, exceeds $121,759.
Data Scientist Salary San Francisco
Location is one of the biggest factors that affect data scientist salary. In fact, average salaries differ significantly within the US. In certain areas, data scientists earn much more than the national average. Take the average data scientist salary in San Francisco, for example, which is $124.570- 29% higher than the national average. The pay is also higher in Seattle (by 15%, to be exact), and Boston (5.0%). The average data scientist salary in NYC can also be quite impressive. On the other hand, the lowest salaries reported by Escala salarial can be found in Chicago (5.4% less) Washington, D.C. (5.3% less) and Atlanta, Georgia (4.9% less).
Otros factores que aumentan los salarios
The impact that the level of experience and location have on average salaries can’t be ignored, but there are other factors that count too. Before taking a closer look at the additional skills that are likely to increase the average salary, it’s also worth considering specific employer requirements and their own standards. To give you some examples from popular companies:
- Average Facebook data scientist salary ranges from $123,651 on Escala salarial, to $143,860 according to Glassdoor, and even $180,378 as seen on En efecto
- Average Google data scientist salary, on the other hand, is quite consistent: $136,909 on Escala salarial and $139,792 on Glassdoor
- At the same time, there are very few sources on the average Amazon data scientist salary. As stated by Glassdoor, it amounts to $122,138
Popular additional skills
- Complex problem-solving skills
- Expertise in all phases of data science (from initial discovery through cleaning, model selection, validation, and deployment)
- Familiarity with a wide variety of data sources, including databases, public or private APIs and standard data formats, such as JSON, YAML, and XML
Competencias adicionales útiles
- Coding skills, such as R, Python, or Scala
- Ability to apply aprendizaje automático to business processes to improve their efficiency and effectiveness
- In fact, skills in machine learning and Python are correlated to pay that is above average
Data scientist responsibilities
Generally speaking, data scientists are responsible for:
- collecting large amounts of “raw” data and transforming it into a more comprehensible format
- solving business-related problems by making data-driven decisions
- looking for patterns in the available data
- spotting trends that can help a business’s bottom line
The exact tasks they perform depend mostly on their level of experience, knowledge, and skills, as well as their location and their employer’s requirements.
Conclusión
The demand for data scientists has been growing over the years, as increasingly more companies want to tap into the power of big data and make good use of it. The more data scientists are needed, though, the more challenging it becomes to land the best candidates with the right skills and experience. Make sure you’re ready to offer a competitive salary and screen your candidates properly.
Antes de partir
También disponemos de otros magníficos recursos dedicados al salario de un desarrollador de software, como:
