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There are 7 easy steps you can follow to organize a compelling data science cover letter:
- Write your contact information at the top;
- Address the right recipient by name;
- Craft a memorable introduction;
- Demonstrate the value you can add to the company in a short and direct body paragraph;
- Devise an effective closing paragraph with a strong call-to-action;
- Use a professional sign-off.
- Proofread (and then proofread again).
We already walked you through the first steps to writing a great data science cover letter. So, now it’s time to focus on the essential elements of your cover letter and the content that will make it shine.
What to include in a data science cover letter?
How to Organize a Data Science Cover Letter: Contact Information
Do you know what hiring managers hate? Rummaging through the content of a data science cover letter to find your contact information. So, do them (and yourself) a favor and put your name and contact information at the top. The easier you make it for your potential employer to reach out, the better. Your contact information should include your name, phone number, and a professional email with your first and last name. Clean and easy-to-find.
How to Organize a Data Science Cover Letter: Opening/Greeting
This is your chance to make a great first impression. Whatever you do, don’t start with “To whom this may concern”. It will make you look sloppy and unprofessional. Instead, do your homework and find out who you’re addressing. Yes, it may take some phone calls and a few Google or LinkedIn searches. However, it’s worth the effort, especially if most candidates have written a blunt generic opening.
Now, depending on the company culture, you could address the recruiter/hiring manager by their first or their last name.
But what if you can’t find the hiring manager’s name?
In that case, go with a safe option like “Dear Data Science Team Hiring Manager”, “Dear Hiring Manager”, or simply write “Dear [Company Name] team”
How to Organize a Data Science Cover Letter: Intro paragraph
Your cover letter introduction should tell your potential employer the following 5 things:
- Who you are;
- Your profession/expertise;
- What role you’re applying for;
- How you discovered the job posting (especially if you were referred by a current employee of the company);
- Why you’re interested in the company/job and what makes you a perfect fit for that position.
However, being informative isn’t always enough. Therefore, an underlying goal of your cover letter introduction is to entice the hiring manager. You want them to keep reading to learn more about you. So, think of a unique opening line that would grab their attention. For example, you can include an impressive achievement of yours.
Even if you have no experience in the field, and you’re applying for an entry-level data scientist position, you can still make this work.
Just emphasize on your degree, personal or group projects, volunteering, and relevant certifications. Another way you could go is to mention an important accomplishment or recent success of the target company (or the hiring manager themselves) they’re proud of. If you were referred by a current employee or an important client, make sure you write that in, too. But don’t go overboard with humor or self-praise. Show that you’re enthusiastic about the company. Let them know you’re aware of their needs and you’re following their latest developments. Tell them what you can offer them to help them achieve their goals All the while, Do your best to sound natural and leave the strict formalities behind. Go for simpler words. This will help you achieve a friendlier tone.
How to Organize a Data Science Cover Letter: Body paragraph
This is the most crucial part of your data science cover letter. Fortunately, there are a few rules of thumb that will help you present yourself in the best light possible:
Less is more
It’s easy to get carried away when you want to make a good impression. But there’s a thin line between showcasing your skill set and just bragging about your accomplishments. Be short and direct. And only include meaningful achievements in light of business success you can provide relevant context for.
Don’t copy your resume
…But do borrow some tangible metrics from it, especially when it comes to relevant projects you’ve worked on and the impact you’ve had on achieving your current/former employer’s business goal. It’s a numbers game, so make sure you quantify the results you’ve accomplished.
Show you’re the solution to their problems
Employers hire people to solve specific challenges. It could be improving an algorithm for an AI-powered app; or implementing changes to their database management system to increase efficiency… Or increase their revenue by developing a machine learning solution from scratch. Whatever it is, it’s your job to research the urgent business needs of the company. Once you’ve discovered their pain-point, explain how you can use your expertise to help. You can even take it one step further by finding information about the company’s future goals. Then use your relevant work history to prove you can help them get there.
Use the job description to your advantage
Make no mistake, Applicant Tracking Systems (ATS) will leave no word in your data science cover letter unchecked. So, incorporate as many keywords from the job description as appropriate. In fact, this is the part of writing your data science cover letter where direct copy-paste is highly encouraged. Just go right ahead, it’s guilt-free!
Work experience isn’t everything
Are you a recent graduate with no professional experience in data science? Keep your chin up because you still have plenty to offer. When it comes to entry-level positions, employers look for 3 things – suitable education, skills, and desire to learn quickly. Focusing on these in your data science cover letter will make up for the lack of 5-page work history.
In case you’re transferring into data science from a different field, emphasize on the data science certifications and skills you’ve acquired. These not only open the door for you, but also demonstrate a commitment to your new profession. (Data science isn’t a field you can enter without any relevant qualifications, so additional courses and online trainings are key). There’s also something else you can capitalize on – your transferrable skills. So, refer to your data science resume and include the most suitable examples for the particular job posting. And don’t forget to mention the reason for your career change. Your potential employer will appreciate that you’re proactive and enthusiastic about what you do.
Show some personality
Your data science cover letter isn’t just a supplement to your resume. It’s a brief story about who you are, how you can make a difference, and why you’re the perfect fit for the job. So, let your personality shine through. Add a layer to your cover letter by touching on certain interests that relate to the role; hint at your sense of humor; share a particular detail you like about the company and their culture… Anything that will make a really good story of what makes you “you” in your working life.
How to Organize a Data Science Cover Letter: Closing paragraph
The closing paragraph in a data science cover letter serves a two-fold purpose:
- To remind the employer why you’re the best candidate for the job;
- To prompt the employer to get in touch with you with a concrete call-to-action.
Make it clear that you’ll be happy to be interviewed. You can also tell them that you’ll follow-up in a week if you don’t hear back. And, of course, don’t forget good manners – thank the hiring manager for taking the time to read your cover letter.
Sign-off
Your sign-off should be sharp and professional, just like you. Anything other than “Sincerely”, “Regards”, and “Best regards”, followed by your first and last name, would be redundant.
Proofread
How to proofread a cover letter? A typo or a spelling mistake in your data science cover letter can cost you the interview. That’s why we prepared a list of proofreading tips you can use to submit a polished and mistake-free cover letter:
See it in print
Printing out your resume in a larger font is a legit strategy for catching errors, missing punctuation marks, and even text inconsistencies. You can highlight the edits you need to make with a colored pen. This way, you’ll find the changes easily once you get back to your cover letter file.
Your voice is your top editor
Reading your data science cover letter out loud might feel awkward, especially if there’s no love lost between you and the theater. However, that’s one of the best ways to detect bad phrasing and spelling mistakes. And it’s so much better to notice them before your potential employer does, right? Once you’ve finished your monologue, you can read your cover letter out loud once again. Only this time, start from the bottom to the top. It’s fun and it will help you spot that one typo you’ve previously missed.
Phone-a-friend
Everyone has that one spelling-bee friend. So, why not put their talent to good use and ask them to review your cover letter? Very often, it takes seconds for an extra set of eyes to spot an error you weren’t even aware of. Once your data science cover letter has passed this final test, you can finalize your proofreading efforts with some free tools like Grammarly, ProWritingAid or WhiteSmoke.
Your data science cover letter is a powerful tool in your job application process.
Now that you know how to organize it and fill it in with killer content, make sure you check out the rest of our articles on the topic:
How to Write a Data Science Cover Letter
How to Format a Data Science Cover Letter
Data Science Cover Letter Dos and Don’ts
Curious to discover what the data science interview has in store for you? Visit our detailed guide Data Science Interview Questions and Answers You Need to Know in 2020.
And, if reading this piece helped you identify some key skills you need to add to your data science toolbox, take a look at the courses in the 365 Data Science Training. You can explore the curriculum or sign up 12 hours of beginner to advanced video content for free by clicking on the button below.
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