Why do you need a cover letter when you write all your qualifications and experience on the resume?
In your data scientist resume, the focus is you – your experience, qualifications, and achievements. However, while ellaborating your achievements in your cover letter, you could also demonstrate how those achievements would benefit your potential employer and why you’re particularly interested in working with them.
It's a tailored document to the job you're applying for. That's why job applications with cover letters have a higher chance of getting shortlisted for interviews.
Writing a cover letter doesn't have to be daunting, at least after reading this guide.
This article includes:
- Data scientist cover letter examples you can copy.
- Guide to write each paragraph masterfully.
- Pro tips for writing the BEST cover letters every time.
Give your data scientist job application a branded look by creating your resume and cover letter both using our resume builder. It won't take more than 15 minutes to create a complete application. Most importantly, they convert well.
Cover Letter Example for Junior Data Scientist Position
Data Scientist
yohangomas@gmail.com
(234)567-8910
California
28 Nov 2022
Katy Williams
Hiring manager
web analytics
California
Dear Katy,
After graduating from California State University with a bachelor's degree in data science, I seek to join a world-class retail company to implement my education and research experience. I specialize in data visualization tools, big data, and machine learning that help retail businesses develop accurate forecasts.
In my internship at Adidas, I created a statistical model that could forecast sales with an accuracy of 97% in 2021, resulting in better regional marketing and business decisions.
I am confident that my skills in statistics, applied mathematics, and machine learning would help your organization achieve tremendous results with accurate forecasts and data interpretations.
It will be my pleasure to discuss with you the specifics of the role in an interview.
Yours truly
Yohan Gomas
How to Write a Data Scientist Cover Letter
The cover letter is your sales pitch to the hiring manager. It should explain your key skills as a data scientist while providing evidence and use cases from your previous data science work experience.
The objective is to create a tailored document that addresses exactly the hiring manager's pain points.
The most common scenario is that your hiring manager first skims through your resume and only opens your cover letter if they are convinced about your profile.
In general, a hiring manager spends about 5 to 7 seconds on an application and your cover letter should grab the attention of the hiring manager in seconds.
The good news is that a great cover letter has a definite structure that anybody can easily copy.
Here's a time-tested cover letter structure for a data scientist:
- Header
- Opening greeting
- First Paragraph: Introduction
- Second Paragraph: Your achievements
- Third Paragraph: Benefits of hiring you
- Fourth Paragraph: Call to Action (CTA)
- Complimentary close
- Postscript if applicable
Let's break it down step-by-step.
Start with the Header
Your cover letter should follow a formal letter structure starting from your information and the receiver's information. If you don't know the hiring manager's information accurately, you can skip them without doing guesswork.
However, a cover letter directly addressed to the hiring manager would be much more effective than one that is addressed as "For whom it may concern." With the help of professional social platforms such as LinkedIn, you can easily find the hiring manager's name.
Keep this section short. Clearly mention your name and contact information.
Examples
Here is an example of a header for a data scientist cover letter.
Data Scientist
dannymorgan@gmail.com
(234)567-8910
New York
15 Sep 2022
Carl Peterson
NTC bank
New York
Opening Greeting
You should start your letter with a greeting. A formal greeting will be the safest option if you don't know the organization's culture clearly.
Always try to use the first name of the hiring manager.
Start by Introducing Yourself
Your first paragraph determines the success of your cover letter. A great cover letter is one that a hiring manager reads until the end. If your first paragraph hooks the reader, they will probably read your full cover letter.
So how to write a killer first paragraph?
Briefly summarize your key skills and achievements in your first paragraph. This could be two sentences describing the essence of your career.
However, what most candidates do here is write a career history from their education to their recent job experience. Remember, this is not your biography, and the hiring manager is not interested in reading that. They want to see what you have for them – real fast.
Examine these examples:
Having 7 years of experience in the data science field working for one of the top entertainment companies in the UK, received the award as the best data science research paper in 2021 for developing a data model for music consumption habits of Gen-Z users.
I completed my bachelor's degree in computer science at The State University of California in 2017 and read for my master's in data analysis. I started my career as a data analyst at WPK holdings analyzing their investment portfolio and retail business. After 2 years working at WPK, I joined AquaTech as a senior data analyst.
The first sentence on your cover letter is important. In the above examples, when the hiring manager starts reading the INCORRECT example, they already get bored seeing you start from the beginning of your career/ education.
Describe Your Achievements
Talk about the specifics of the projects you were involved in – the problems you solved – and the results you achieved.
Make sure the projects you write are related to the skill requirement of the data science position you're applying for. Catch the attention of the hiring manager by using numbers.
Here's an example:
At Kmart, analyzed their customer purchasing data to create a forecasting model for each client with an accuracy of 67%, which was used in purchasing products in 2021 resulted in a 12% increase in overall sales while 17% drop in stock.
As the data analyst at Kmart, I was responsible for analyzing customer purchasing data and coming up with data models that describe those raw data as meaningful information for management to make important business decisions.
In the CORRECT example, the hiring manager gets a quick idea about your performance, such as achieving 67% accuracy, a 12% sales increase, and a 17% drop in stocks. Numbers attract eyeballs and communicate ideas effectively.
What's the Benefit of Hiring You?
Now the hiring manager has a pretty good idea about your skills and expertise. It's time to address their pain points – why should they hire you?
Do your research. Find out why they need a data scientist in the first place. This is important for two reasons: you can have an idea about the type of work they'll expect from you, and you can address them in your cover letter.
They usually state their hiring objectives in the job advertisement. Describe what problems you could solve using your expertise in data science.
There is no better candidate for a job than one who really understands why they are being hired.
With my in-depth knowledge of data structures and applied mathematics, together with my excellent communication skills with a wider professional audience, it would be an exciting time for us to solve problems and improve business processes at Kmart using data.
I am confident that I would be a great addition to your team, considering my technical skills and soft skills.
Finish Your Data Scientist Cover Letter With a Call to Action (CTA)
End your last paragraph with a call to action. It could be as simple as asking for an interview to discuss the job further. Show your interest throughout. You can use this space to communicate your availability for interviews as well.
It will be my pleasure to discuss with you my role as a data scientist and demonstrate how my previous experience can easily be incorporated into your project for greater success.
I look forward to hearing from you at your earliest convenience.
Do not think about this as an interview. It's a meeting you're having with your future potential employer to know more about them. They have the same interest and objectives for this meeting.
To speed up the process, indicate that you're open to a quick informal interview or a phone call. Hiring managers want to close the positions fast with the right candidates. If they're ready, why not you?
The Farewell: Cover Letter Closing
Finish your letter with a standard closing. Be respectful and thankful to the reader.
Consider the following letter closings:
- Yours truly
- Yours faithfully
- Yours sincerely
- Regards
- Kind regards
- Warm regards
- Respectfully
- Most sincerely
Avoid these
Informal salutations might work for some companies depending on their culture. But the risk is not worth taking. Therefore, avoid these:
- Take care
- Ciao
- See you
- Cheers
- Fondly
Tips To Improve Your Data Scientist Cover Letter
Write a winning cover letter every time with these tips.
- Do your research: Do not limit your research to the job description. If you're really interested in the job, further your research – analyze their business model – find out about their target market – identify why they want to hire data scientists. This information will help you write better cover letters.
- Keyword research: Find out the right keywords to include in the resume and cover letter. Start your keyword research with the job advertisement. Refer to their website, relevant blogs, company’s LinkedIn account, and industry news.
- Keep it formal: Make sure your cover letters are formal. Avoid using slurs, casual language, or abbreviations. Use a modern cover letter template for best results.
Key Points: Writing a Data Scientist Cover Letter Masterfully
- Choose a matching template for your cover letter. Use the same one that you used for the resume.
- Start with a layout in place.
- Start your cover letter as you start any formal letter.
- Give a summary of your data science career, achievements, and education in the first paragraph.
- Demonstrate your key achievements relevant to the job in the second paragraph.
- Showcase how you would fit their requirements in the third paragraph.
- End the cover letter with a CTA – request a meeting or an interview to discuss further.
Complement Your Cover Letter with a Resume
Your job application consists of two main components: a resume and a cover letter. Your cover letter and resume should complement each other.
A well-written data scientist resume will still be the main part of your job application. Most hiring managers first read your resume.
Your resume should include a professional summary, education, skills, and experience sections. Try to relate your experience and skills as much as possible to the job and the organization you're applying for.
Sometimes, your resume goes through ATS, and the recruiter will read only the shortlisted data science cover letters. Therefore, it's important to optimize your resume for keywords.
Try using our resume builder to create your data scientist resume and cover letter with the help of modern templates. Save your time. Apply for 10 times more data science jobs in a day.
FAQs
Is a cover letter necessary for a data scientist?
Some job advertisements explicitly mention you to include a cover letter. However, including a cover letter would be a great addition to your resume.
Your data scientist resume aims to communicate your experience, achievements, and educational qualifications to carry out the job.
The cover letter serves a different purpose. It conveys your passion and interest in the field while providing the hiring manager with a solid reason to hire you.
If you're really interested in a certain job, write a cover letter together with your resume, regardless of whether they ask for it or not.
What does a data scientist do?
The job of a data analyst is to analyze data and create meaningful information out of them for the technical, management, and marketing teams to make better business decisions. For this, they use mathematical models, statistics, and machine learning.
Apart from the tools and software, a data scientist needs to be skilled in basic software engineering and should have a solid business, finance, and technical background.
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