We are amid a pandemic that has left millions jobless around the world. It has become difficult to have a budget to hire data scientists, engineers, data analysts, or artificial intelligence experts.
But if we can hire – this is a great time to be up-skilling our data teams!
More candidates, better depth of skills and experience: There is a wider range of candidates to hire from. Startups are letting go of data experts, large companies are letting go of data analysts. Hiring managers are seeing better resumes come across their desks and candidates are more eager to interview.
Covid-19 has already forced most data professionals to work from outside of a fixed office. Can our data scientists, analysts, or engineers be effective working remotely? If so – why not consider hiring them in a different location than planned? The US government’s decision to suspend H1-B visas for the rest of 2020 should also make more data experts available outside of the USA. It should now be possible to hire more skilled personnel and better-experienced personnel working remotely to fill openings in data.
There is no reason today to hire people in an expensive location, as long as they have a good Internet connection and are able to work on a time-zone convenient to the organisation.
Selective skill shortages: Not all skills are becoming more available – those that enable remote work are becoming harder to find! Remote work generally means doing more in the cloud. As more companies need to move towards the cloud, software, and data engineers working on cloud-based data pipelines are in high demand. Automation skills in the space of data are another difficult to find skillset.
In general, hiring managers are seeing more resumes and more recruiters with better resumes for each open position. They can afford to be more selective when shortlisting and hiring candidates, but the situation is fluid – I would recommend hiring the best candidates as soon as possible.
Developing Data skills internally: It is never easy to hire experienced and highly skilled Data Scientists or Analysts externally, even in the best of times. Top Machine Learning Engineers are practically impossible to hire in some places. It may be possible to leverage internal adjacent roles sometimes and provide broader coverage while retaining valuable experienced employees.
A software engineer who has been working to help data scientists may be ripe to transition to an ML Engineer role. They may already have the core skills needed and if they know the application domain – they may be a better candidate than an external candidate who has to ramp up on the company and technologies.
An existing, internal data analyst who has the aptitude for machine learning might be willing to partner with an ML expert internally and ramp up their skills while working on immediate and pertinent problems. This might help in retaining top talent while also improving morale and sentiments inside the company. A new employee will take time to ramp up – it is worthwhile looking internally and think outside of the box in hiring.
Covid-19 is here to stay. But since it is raining coconuts, maybe its time to make Pina Coladas! We should use this time to up-skill, hire, or grow our data teams so that we will come out stronger in the future.
Good luck, happy hiring, and tell us how you are doing!
