As the current situation remains uncertain, organizations are becoming increasingly cautious about their hiring strategies. Most firms have either reduced or frozen their hiring activities. According to a news report, this might see a 30% drop over the last year if the current situation continues to persist. And data scientists are not immune to this either.
They are likely to face challenges when it comes to landing a job in these difficult times. Since new job openings are expected to come down, the ratio of jobs per applicant might hit bottom. The number of open job requirements as of April 8 was 98,362 in India, which is the lowest since December 2019. In such situations, data scientists will have to plan better to stand out.
In these times, your visibility can arguably have the most significant impact on recruiters. Jessica Hernandez, president and CEO of Great Resumes Fast, said that in this crowded space, for applicants to get noticed, they need to highlight quantifiable examples of their work. And their LinkedIn profile should not be a duplicate version of their resume. While the classical approach of making an effective resume is still relevant, one must increase their visibility on platforms like LinkedIn, Medium, Kaggle, and more, by sharing their data science work and engaging with the community.
Recruiters will be critical of their achievements and the skills that they mention in the resume. Consequently, they should leverage social, professional, and developer platforms to boost the trust in recruiters through demonstration of their work online. This will provide an edge over other applicants who have applied for the same opportunity.
Referrals From Data Scientists
Referrals are a win-win for both employers and applicants. While the former decreases the hiring cost by tapping into employees’ network, the latter gets a direct opportunity to showcase their skills. However, candidates should try to get referrals from data scientists and not from employees of other domains. A profile suggested by data scientists would bring confidence to the recruiter about their potential in the field. This is where a network of prominent data scientists is significant. They can be leveraged to create endless opportunities.
During economic difficulties, companies do not prefer to increase their headcounts irrespective of the required resources. This is due to the uncertain prospects of obtaining projects. However, since they still need to complete the work at hand, firms look for freelancers who can assist them in their ongoing projects. If not big companies, startups actively seek freelancers to weather the storm caused by economic challenges. Consequently, getting a freelance job can be one of the best bets, if you do not get a full-time job. You can apply for freelance data science jobs here.
Also Read: How to work as a freelancer in data science
Applying For Targeted Jobs
Applying for targeted jobs on platforms like LinkedIn, Glassdoor, among others, will only burn you out. Instead, you should understand the job description of the opening and create a targeted resume to increase your chances of standing out. Applying to every opportunity with a single universal resume might not shed light on your skills that the companies require. Even minimal changes to resume when focused on a specific data science job can make a significant difference. While this strategy is not new, it is critical.
If none of the above strategies works for you, then you should seek personalized help to understand what you lack and how you can improve. For this, you will need to take guidance from mentors who can assist you in shaping your career. “One can succeed by solely depending on their understanding and taking decisions accordingly, but a mentor can assist in reducing the number of roadblocks one would hit otherwise,” says Bastin Robin, a chief data scientist at CleverInsight. To get mentors assistance, you can either use your network or can register in the AIM one-on-one mentorship network.