Poll Results: Data Scientists don’t stay long in their jobs
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Job market for Data Scientists is hot - half of them left their previous job after 2 years or less. In a hopeful sign for employers, Data Scientists plan to stay longer in their current job, for all job types.
The latest KDnuggets Poll examined How long analytics/Data Science professionals stay at their jobs.
The results show very strong volatility, with half of voters saying they stayed at the previous job 2 years or less. Because of the long tail, the average stay at a previous job was 3.4 years. In a hopeful sign for employers, Data Scientists plan to stay a longer at their current job. Poll question
Fig 1. Length of Stay at previous vs current Analytics/Data Science Job
Among job types, we see big pull from industry and increase in self-employed, and decline in academia.
Also, 13% had no previous job and majority of them went to the industry as well.
Next we examine how long Data Scientists stayed at their job by job type.
Fig 2. Length of Stay at Previous Analytics/Data Science Job by job type
We note that industry median length of stay at a previous job was around 2 years,for academia around 2.5 years, for Govt/ non-profit around 3 years, and for Self-employed/ Consultants ~1.5 years.
Next figure looks at how long Data Scientists plan to stay at their current job, broken by job type.
Fig 3. Expected Length of Stay at Current Analytics/Data Science Job by job type
Here median length of stay increases for all job types:
Next chart compares the previous and current job stay for industry and academia - we see a lot fewer industry people planning to leave current job in less than 1 year, and a lot more planning to stay 4-8 years.
Fig 4. Previous vs Expected Current Length of Stay at Analytics/Data Science Jobs for Industry and Academia
Poll regional participation was
Related:
The results show very strong volatility, with half of voters saying they stayed at the previous job 2 years or less. Because of the long tail, the average stay at a previous job was 3.4 years. In a hopeful sign for employers, Data Scientists plan to stay a longer at their current job. Poll question
How long do you expect to stay (from time you started) in your CURRENT analytics/data science job?had a median answer of about 3 years, and an average of 4.5 years.
Fig 1. Length of Stay at previous vs current Analytics/Data Science Job
Among job types, we see big pull from industry and increase in self-employed, and decline in academia.
| Job Type | Previous Job | Current Job | Change |
|---|---|---|---|
| Industry | 57.7% | 75.6% | 31% |
| Academia | 11.4% | 5.4% | -52% |
| Government/non-profit | 7.3% | 6.0% | -19% |
| Self-employed/Consultant | 4.3% | 7.0% | 63% |
| Student | 5.4% | 1.9% | -65% |
Also, 13% had no previous job and majority of them went to the industry as well.
Next we examine how long Data Scientists stayed at their job by job type.
Fig 2. Length of Stay at Previous Analytics/Data Science Job by job type
We note that industry median length of stay at a previous job was around 2 years,for academia around 2.5 years, for Govt/ non-profit around 3 years, and for Self-employed/ Consultants ~1.5 years.
Next figure looks at how long Data Scientists plan to stay at their current job, broken by job type.
Fig 3. Expected Length of Stay at Current Analytics/Data Science Job by job type
Here median length of stay increases for all job types:
- for Industry jobs increases to ~3 years
- for Academia goes up to ~6,
- for Govt/ non-profit goes up to ~4 years,
- and for Self-employed/ Consultants goes up to 4 years.
Next chart compares the previous and current job stay for industry and academia - we see a lot fewer industry people planning to leave current job in less than 1 year, and a lot more planning to stay 4-8 years.
Fig 4. Previous vs Expected Current Length of Stay at Analytics/Data Science Jobs for Industry and Academia
Poll regional participation was
- US/Canada, 51%
- Europe, 26%
- Asia, 13%
- Australia/NZ, 4.3%
- Latin America, 3.8%
- Africa/Middle East, 1.6%
Related:
- How Long Should You Stay at Your Analytics Job?.
- Stop Hiring Data Scientists Until You're Ready for Data Science.
- 5 questions to decide if you need a data scientist.