Stop Thinking. Start Applying.
It’s already the end of February, and for those of you who are looking for internships or jobs in Data Science, there can’t be a better time to start the daily routine of applying to 50 Companies! Just kidding.
It is quality rather than quantity that matters.
Even if you haven’t started, it is not late. But, it’s not too early also. As you are reading this, there are people who are giving interviews for those companies that you seek to target.
Find out what you like doing best and get someone to pay you for doing it. - Katherine Whitehorn
After my last post where I urged you to start learning, here, I request you to start applying, because industrial exposure matters.
Finalise your Resume
The most important tool you have on your resume is language.
When you apply for a position, you are basically selling yourself to the company. This is is the place where you get maximum opportunities to market your capabilities.
- Stick to a one-page resume. Very important. Nobody wants to read that you won a fancy dress competition in 5th Standard.
- Pick a light-colour design. It should carry a corporate look.
- Spacing is the key. It shouldn’t be too cluttered.
- Explain related work, and not just any work.
For the second yearites who haven’t done much till now but want to apply, mention courses that you have completed, or data science problems as projects. Here’s Elon Musk with his one-page brief:
Spend 4–5 days in building the resume. Ask for suggestions from people near you. Perfection isn’t achieved in one go.
Drafts after drafts, you’ll get the right one!
Write Cover Letter
To find out your real opinion of someone, judge the impression you have when you first see a letter from them.
What most people ignore is the value of the cover letter. They write total crap in there, and expect to get a call.
It sets the stage and introduces you to the reader. It is where most of the good candidates tip the scales in their favour.
- Be to the point. Don’t beat around the bush. Focus is key. Align your capabilities with the employer’s requirements.
- Establish brand. Make him believe that you are above-average. Nobody hires average ones.
- What added value you carry? Tell that.
- To clinch the victory here, set the stage by mentioning your USP.
It should be roughly one-page long, or around 200–300 words.
P.S. - DON’T write generic cover letters to all employers. Read about Research in the next section, and accordingly draft the letter out.
Research about the Employer
I have hardly seen anyone spending time on this. But, believe me, it matters!
Eg. You are applying to a healthcare industry which delivers medicines to people’s homes. What would they prefer?
- A candidate who says he is interested in data science and wants to join.
- A candidate who gives inputs as to how data science can be further exploited by the company.
Spend a week or so in knowing what the employer does, how he does it, and what are they expecting from a person right now!
- Customised mails catch eye rather than standard ones.
- Who doesn’t want a candidate who is thorough with his reasons for joining.
Show Time!
Once you have done research, and are ready with the resume and cover letter, it’s time to come to the battle field and fight out for that job!
- GitHub Profile: For Data Scientists, employers are interested to know what work they have done till date. Try and keep your GitHub updated with whatever you do. Efforts shouldn’t be hidden. Right?
- LinkedIn: There are many companies these days who post their vacancies on LinkedIn. Make sure to register there, and apply.
- AngelList: Actual learning happens when you intern at a start-up. For those of you interested, this is the place.
- Mailing: Conventional way of apping is not out of fashion, just yet. Find the companies and mail your resumes along with the letter, to their careers@xyz.com or jobs@abc.com.
If you aren’t getting rejected on a daily basis, then your goals aren’t ambitious enough.
Now, you people may have questions regarding what is asked in Data Science interviews? Let’s keep it for some other day.
As it is, first start with resume-building. Meanwhile, I shall work on that post. For starters:
- DeZyre - 100 Questions
- AnalyticsVidhya - Favourite 40
- Springboard - 109
- Data Science Central - 66 Job Questions
So, stop thinking of applying, and start RIGHT NOW! It’s never too early.
If you have any suggestions, don’t hesitate in commenting. :)
And, ❤ if this was a good read. Enjoy!
