With our latest article on ‘data science and analysts jobs,’ it has been established that the data analytics jobs market is continuing to look up despite the worst recession hit of all time. That being said, although companies have quickly adapted themselves into the virtual hiring process, starting a career virtually, amid global pandemic, can be a challenging task for new data science graduates.
Initiating a career in data science is itself difficult, however, with the prevailing situation, virtual onboarding can make it even more difficult for newbies who have just entered the most competitive field of the current time. Traditionally the hiring process of data scientists comes with orientation, sharing business vision, in-company training, as well as healthy interaction with senior data scientists of the organisation. But, with virtual onboarding, many companies aren’t equipped to reproduce the same in this situation.
Furthermore, the COVID pandemic has brought in a massive change in data, even in terms of quantity, with humans changing their outlook amid the crisis. This put new data scientists in a critical position to bring better business outcomes, which can be challenging in the current situation.
So if you are a recent data science graduate and lucky enough to start a career amid this global downturn, this article might be for you. Here, we will share a few tips that can help recent data science graduates to navigate through the complexity of virtual onboarding as well as help them settle in their new role with high expectations.
Be Prepared For The Situation
One has to be extremely patient while starting their data science career amid this global pandemic. Not only because the processes will be slow, but also because the expectations will be high. With businesses working with a massive amount of data as well as looking for resources to cut down costs, hiring data scientists need to seem fruitful for the company. Thus data scientists need not be prepared for just looking for a job in the normal situation, but they should add some outstanding achievements to their profiles so that they can be recognised uniquely in the crowd.
Developing data science strategies for better business is a challenging task itself, and with overflowing data and changing customer patterns, the task becomes even more difficult. Thus, to keep themselves prepared and updated with industry trends data science graduates should take part in hackathons, work on building outstanding portfolios, gain some certifications, and make some live web applications to showcase their skills. For hackathons, they can use platforms like Kaggle and Machine Hack to flex their NLP, CV and deep learning muscles, whereas to build their portfolio, they can leverage GitHub as well as Kaggle. Alongside, these graduates have to work on model deployment in their new organisation, thus should learn Microsoft Azure or Google Cloud.
Applied Data Science Practice
On-field training has been a critical part of a data scientist’s career, but working from home restrains that possibility for many. Thus for a data scientist to continuously thrive in this ever-evolving landscape, it is necessary to be updated with relevant knowledge. And that’s where upskilling comes into the picture. For this, these graduates can take help of MOOCs, online classes or even crash courses to brush up their skills continuously. Upskilling or reskilling will not only help data scientists to sustain in their new job but will also help them grow their career, despite the recession.
Furthermore, data science jobs come with a lot of complexities, which can be either solved by the experienced colleagues of the company or one should try their hands on applied ML/DS practice. This will help them get their hands-on training with real-world organisational and industry-specific analytics scenarios.
Over Network To Fill The Gap
Besides other things, the lockdown has disrupted, one is the in-person communication between data scientists in organisations. Data scientists themselves tend to work in silos, and with work from home scenario, networking takes a back seat. With new joiners starting their career virtually in an organisation, it is critical for them to over-network to fill the in-person gap.
To facilitate this, new data scientists should firstly keep their LinkedIn profile updated, for the network to highlight their skills and projects worked on. Additionally, LinkedIn can be a perfect platform for these graduates to network with other data scientists of the field. Along with that data science graduates can also attend virtual events like CVDC, Kaggle Days, etc. to network thoroughly with the attendees with similar interest.
Furthermore networking within the organisation is also critical for data science graduates. This will not only help them understand the business from an experienced point of view but can also gain assistance in solving complex business problems, which can be challenging for amateurs.