“Why do I need to write a data science cover letter?”
Even if it isn’t listed as a prerequisite, a data science cover letter can still be a vital step in your job application process.
A well-crafted data science cover letter has the power to distinguish you from the crowd. It speaks volumes about you as a professional. What’s more, it creates context around your resume and lets the potential employer see beyond the bulleted lists with qualifications and accomplishments.
If written properly, a data science cover letter gives insight into your personality and shows how you’ll fit the company’s team and culture. But, most importantly, it gives you a chance to address a company’s pain-point and demonstrate you have what it takes to offer a solution. And that’s precisely what can move your application to the top of the pile.
So, how to write a successful data science cover letter?
This thorough data science cover letter guide will help you build a cover letter to land a job in data science from scratch. It will take you through all the necessary steps:
- initial research and target job deconstruction;
- sections and content of a data science cover letter;
- data science cover letter formatting;
- tips and mistakes to avoid when writing your data science cover letter.
So, quit staring at a blank page wondering what to write. It’s time to call your great storyteller alter-ego and get down to it.
How to Write a Cover Letter for a Data Science Job?
A great data science cover letter should convey that you’re the perfect fit for the company. But you can’t create that impression if you’re not an expert on your target company first, right? So, before you start writing, here’s the initial step you need to take.
Research the company
That’s a must for any job candidate. But it’s especially important in the data science field. Why? Because data science serves a lot of industries. So, you must be informed about how things go down in a variety of businesses, be it security, stocks trading, food innovation, or consulting. Moreover, you should be familiar with their main competitors on the market and the technology your target company uses. And yes, there are clever ways to incorporate this knowledge into your cover letter. (And we’ll discuss how to do that to score yourself some extra points later in the article.) Fortunately, there are plenty of places where you can find all the information you need.
Why Start with the Company’s Website?
The company’s website is the first place you should look. Because it is all in there – services, projects, product descriptions, news… And of course, the “About Us” page and the company’s Mission Statement, where you can find out more about the company culture and their core values. So, here’s a quick tip: just learn these by heart. Then make sure you mention some central details in your data science cover letter. That’s how you’ll prove your avid interest in this particular job opportunity at this company. After all, no employer wants to be just one out of many.
Spoonshot’s constant commitment to leveraging AI technology to help solve the F&B industry biggest challenges is why I’m so excited to apply for this position. My 3 years of experience in the food industry and my passion for data-driven research for answering hard questions with data have always driven me forward in my ambition to develop novel techniques to understand food data and build applications to address business problems.
Stackshare, G2 Track or similar sites:
Stackshare and G2 Track are crowdsourced platforms where companies’ team members share the technology they use in their workplace (Including top Fortune 500 companies like Amazon and Walmart). You can explore the company profile to find the application and data tools, utilities, devops, and business tools it employs on a daily basis. And, if you’re proficient in any of those, definitely add it to your data science cover letter.
With 3 years of experience in Tensorflow and Pytorch, I am confident I will be an excellent fit for Cinnamon’s next AI Research Engineer. My hands-on experience in infrastructure construction (AWS, GCP, Docker) and understanding key Machine Learning concepts has provided me with the innovative and technical skills necessary to successfully provide your company with appropriate technical solution approach to client issues.
Don’t forget to check out the company’s LinkedIn, Instagram, Facebook, and Twitter. These will get you up to speed with their latest projects and upcoming initiatives. Moreover, it might also give you a sneak peek into some recent team events and help you a sense of what the company culture is like.
If you’re applying for a job at a publicly traded company, their annual report is a real gold mine. That’s where you can get an insider’s look at the industries the company is involved in, their business segments, a management’s discussion and analysis (MD&A) of the business financial condition… and even results over the past couple of years. You can also find the list of the board of directors, and executives, along with their occupations. In addition, the annual report shares details about their product lines, operating locations, and project leads. Not only is that a bonus for your cover letter, but it will also inform your data science interview preparation.
Read through the job description to tailor your cover letter.
This is super-important. Similar to your resume, you should target the data science position or internship you’re applying for. This doesn’t mean you should go overboard with self-praise. Just tie your skills and education to the company’s business goals, or to a pressing issue you believe you can solve.
I know that HEALTH[at]SCALE’s current plans involve designing and implementing new predictive machine learning and artificial intelligence algorithms to improve outcomes and economics of care. This project is a perfect match for my interests and an exciting opportunity to identify and formulate analytical problems underlying major healthcare challenges and match the world’s patients to the best treatments possible. I would be happy to leverage my knowledge of machine learning, optimization toolkits, Python, and R to achieve groundbreaking results with this initiative.
How to organize a data science cover letter?
This is the most essential part of writing a great data science cover letter. Your cover letter must be coherent and impeccable. Each paragraph should be well-thought-out to serve a particular purpose. So, you need an opening directed to the right person, an introduction that creates interest and curiosity, body paragraphs that bind your qualifications and skills to the company’s targets and plans for development. And, last but not least, a strong closing paragraph with a must-have call to action. Continue reading…
How to format a data science cover letter?
Formatting can speak louder than words. Therefore, a clean and stylish cover letter consistent with your resume exudes professionalism and a serious approach to the job application process. Luckily, there are simple rules you can follow to create an elegant and sharp cover letter. Continue reading…
Data science cover letter samples
Writing and formatting a data science cover letter from scratch can be a bit daunting, especially if you’re fresh out of college or you’re transferring into data science from a different field. So, to help you out with that task, we’re sharing cover letter samples for 5 of the most sought-after jobs in data science: Data Analyst, BI Analyst, Data Engineer, Data Architect, and, of course, Data Scientist. Continue to data science sample cover letters and downloadable templates:
- Data scientist cover letter template
- Data analyst cover letter template
- BI analyst cover letter template
- Data Engineer cover letter template
- Data Architect cover letter template
Data science cover letter tips and mistakes to avoid
There are certain things that can make or break a cover letter. By all means, your cover letter should be succinct; explain what you bring to the table; and underscore the strong sides of your personality. But what are the other do’s you should strive to have? And, more importantly, what mistakes should you steer clear of? Continue reading…
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