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Much like data analysis itself, writing your data analyst cover letter is both an art and a science. Fundamentally, it should expand on projects that demonstrate skills or responsibilities highlighted in the job description.
Your data analyst cover letter is the place to show off! Read the job description of the job you’re applying to and write down any projects that even vaguely come to mind.
An effective cover letter talks specifically about the company you are applying to. You should aim to make the case to the reader that you have the perfect background for the job.
These 2 data analyst cover letter samples talk specifically to the responsibilities listed in the job description so they’re a great place for you to get started.
A great data analyst cover letter is one that is customized for the role you’re applying to. 95% of cover letters are generic with just the company name replaced.
If you take the time to craft your data analyst cover letter for each job and company you apply to then you’ll increase your chances of getting an interview drastically.
The hard truth is that not all companies actually read cover letters, but the ones that do really care about them. So from an expected value perspective, it’s worth the effort!
Since each of your cover letters should be customized for the job you’re applying to, it’s best to do basic research on the role and the company.
I promise this takes no more than 15 minutes and is well worth the effort.
How to prepare to write your cover letter:
Job Title: Marketing Data Analyst
About Company: SmartAsset is an award-winning financial technology company pursuing the singular mission of empowering people to make smart financial decisions. Recently named one of Y Combinator's Top 100 companies of all time, we have raised more than $50 million in venture capital. Our personal finance tools, calculators and content reach more than 45 million people each month.
Responsibilities of data analyst in job description:
As someone who has spent the last 5 years trying to improve her financial literacy, I am intimately familiar with the value SmartAsset provides. I used your retirement calculator to help set my 401k contribution rate after I graduated college. Improving financial literacy is the best vehicle to address income inequality and I would love to help SmartAsset in that fight as a data analyst.
When a company is scaling its growth one of the most difficult challenges is setting up proper marketing attribution to properly assess the efficacy of each marketing channel. During my time at Sensio Marketing I was instrumental in developing real-time dashboards showing the ROI of ad spend across channels. This required coordination between data engineering to create query-able databases, marketing to understand important KPIs, and myself to test different attribution models and create dashboards. This attribution framework helped our team increase paid ad spend ROI by over 29% year over year.
Data without context can be misleading. In my past roles as a data analyst I’ve placed an emphasis on telling a story with data instead of just building reports. Recently in my marketing data analyst role at Chegg I worked closely with the user research and product marketing teams to build a funnel detailing where users were dropping off in the flow to view questions. Through user research we collected qualitative data that informed us of potential drop off areas. Then we tested versions of the product to address those areas to determine the impact to conversion rate. Iteratively, over the course of 8 months the conversion rate improved by 171%.
Once reports are live and they’ve been tested to verify utility for the proper stakeholders, I tend to implement automation to streamline the creation of the reports and reduce errors. I’d like to help the team at SmartAsset automate as many reports as possible to reduce hours spent fetching, preparing, and visualizing data. This means more time to work on higher value projects. Plus, in my experience there are significantly fewer errors in reports that have been automated.
I am really excited about the prospect of helping SmartAsset reach more people like myself who are struggling with what to do with their finances as early professionals. Through accurate attribution, product analytics, and automation I think I can help the marketing team reach more potential users.
When you’re looking for your first role as an entry level data analyst it can seem difficult to talk about projects related to the job description in your cover letter.
Fortunately, you can make your personal or school projects the focus of your cover letter. When you’re entry level, hiring managers want to know you have the requisite technical skills to be a data analyst.
You should be specific about the tools you used in your projects to really demonstrate you know them well. When used in combination with your resume, you’ll paint a clear picture that you will make a great data analyst.
Just to really hammer home the point I’ll say it again, customizing your cover letter for each entry level data analyst role you apply to is the only way to create an effective cover letter.
No templated cover letter where you just replace the company name is going to read like anything other than boring and generic. Take the extra 45-60 minutes to write a customer cover letter.
Entry level data analyst job openings regularly get 100+ applicants. You should try to take advantage of every opportunity to increase your chances of landing an interview.
Job Title: Entry-Level Data Analyst
About Company: Founded in 2012, Peloton is an innovative tech company that brings members the best workouts possible, all from the convenience of their own homes via the Bike, Tread and iOS App platforms. Peloton uses technology and design to connect the world through fitness, empowering people to be the best version of themselves anywhere, anytime.
Responsibilities of entry level data analyst in job description:
During the pandemic I really struggled to maintain my exercise routine due to the unavailability of gyms. Products like Peoloton are essential to meeting would-be exercisers where they’re at. Social, on-demand exercise helps people feel connected even when not together. I want to help Peloton more effectively reach customers by creating accurate reports as a data analyst.
During college, I participated in a weekend hackathon and co-founded a social movie rating web app with a programmer friend of mine. Creating movie recommendations for users required compiling and reconciling data from multiple sources including boxofficemojo and rotten tomatoes. After reconciliation this data was stored in a MySQL database.
As this social movie app grew from 10 to 1,000 monthly active users I proactively identified gaps in data collection specifically around marketing. We were spending small amounts on different ad platforms but we weren’t reliably comparing the data. I centralized this data and created automated reporting to show the cost per user for various ad channels. This improved the effectiveness of our paid ad campaigns by 8%.
Through my experience with this web app and in my classwork I have consistently demonstrated an eagerness to learn new tools and technologies. I started playing around with Excel to improve my fantasy football teams and many frustrating hours later Excel is now my go-to tool. When I wanted to build a voting prediction engine for our school government elections I tinkered with Python and SQL so I could collect data from the web and store it for use later.
I am thrilled at the potential opportunity to translate my experience working on personal data projects into helping inform product and marketing decisions at Peloton. I want to help keep Peloton analytics accurate, up-to-date, and useful.