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- Budget: According to Glass door, if we talk about the average salary for a data scientist in London is $45,000 excluding national insurance, pension and other profits. Someone having the experience of five years and a PhD degree holder in machine learning is already highly likely to command a high salary and will likely be looking for uplift in earnings when they switch. For most of the organizations, particularly start-ups or SME's, this makes hiring the right talent on a full-time basis and that is relatively expensive.
- Right Talent from the pool: According to the survey, 27% of employers said that the wrong hiring of the candidate will cost them the most. That mistake is quite costly that the HR professionals are bearing. So they should hire the right candidate for the data scientist role by examining their relevant skills. The investment and responsibilities of the data scientist's team will vary from organization to organization.
- Time-Span Involved: Earlier it was quite difficult to hire the candidate for the specific role but when it comes to data scientists that completely impossible to get the right candidate for the profile. But In present scenario this is not as quite difficult now the data scientists with right skillset and mindset can be hiring easily. But still this is the highly time intensive practice.
- Full time or Temporary Basis: Earlier the hiring process was totally focused on individuals, but when it comes to the data science this is not possible to get hire on the basis of this approach because this practice is quite expensive may not necessary that the data scientists have the experience of all the areas for all industries that's why on the permanent basis this practice is quite difficult. And to avoid this most of the organizations are hiring the data scientists for the temporary basis.
- Retention: Right now in all the pointers we are talking about the recruiting or hiring of the data scientists but now hiring is also important but side by side retention is also a huge risk. According to the McKinsey report we will be facing a shortage of 140,000 to 190,000 data scientists by the end of the year 2018. Make sure the data scientists which are on the permanent basis in the organization must be there with the organization for long time.
- Return on Investment for Business: At last every business will talk about the ROI. So after recruiting the candidates, there should be the right use of the resources and make sure to achieve the business goals to run the business long time. The data scientists basically unlock the power of data and this can be completely game changing in the organization. And the companies should train or give induction to the data scientists within the organization only after that the business can earn and measure the ROI.