How to Optimize Your LinkedIn Profile and Resume for a Job in Data Analytics

10 min readAug 6, 2023

I have reviewed a lot of resumes and LinkedIn profiles for people interested in a career in data analytics. Some have been candidates for internships or jobs at my company, or people in my network who want a referral or mentoring or simply feedback on their resume.

There are a few common mistakes I’ve observed when it comes to optimizing your resume or LinkedIn profile for a Data Analytics career.

For the record, I am based in the US, and this advice is targeted to folks applying for non-academic jobs in the US. Other countries/regions as well as academia might have other norms and expectations.

Also, I am just one person. It’s best to consult multiple sources for resume and LinkedIn advice. I’ve listed some more resources at the end.

The Basics

You are not an “Aspiring Data Analyst.” You are a “Data Analyst” who can bring a specific value to a company. Why would a hiring manager want to hire the “aspiring” person when they can hire the person who already views themselves as a professional? Drop “Aspiring” or any similar words from your LinkedIn headline and everywhere else.
Position yourself for the job you want, not your past experience. This is especially important if you are trying to pivot careers. Focus on the experience and skills that are the most relevant to the jobs you’re targeting.
Don’t just describe your jobs with a task list. Focus on accomplishments. What was the impact or outcome? How did you make a difference? Can you quantify your results? More on this below.
Don’t use a fancy template. Keep your resume simple. Here’s a basic template you can use. This is the exact template I use for my resume.
If you’re in the US, don’t put a photo on your resume.
However, use a photo on your LinkedIn profile. Even an illustrated or comic version of a photo of yourself is better than nothing.
2-page resumes are acceptable but typically only for those with 10+ years of relevant experience.
A CV and a resume aren’t the same thing, so if you need a CV for academic purposes, that’s fine, but create a separate resume for non-academic purposes.

Headline

On LinkedIn, your headline is what shows up in search and is the first thing anyone will see. It’s a great opportunities to sell yourself.

The Headline should be short and to the point about who you are. You also want to think about what keywords you want to show up for when recruiters search for candidates.

At the very least, use the format Job Title | Focus Area | Industry, my example: Data Scientist | Product Analytics | Tech. You can also add relevant skills (again, think about the roles you are targeting and what skills are most sought after). I also added a 1-sentence summary of what I actually do. So my full headline is Data Scientist | Product Analytics | Tech | SQL, Python, Experimentation, Prediction, Machine Learning | Providing impact from data to build better user experiences.

About Me

The About Me section on LinkedIn serves two purposes. One is to quickly highlight to your target audience (recruiters and hiring managers) your skills, expertise, and the value you bring to a company. The other is to use keywords that a recruiter might search when looking for candidates.

The About Me section can be 2,600 characters — I recommend putting as much into this section as possible. However, by default, your profile only displays the first few hundred characters, so make sure the first few sentences are the most relevant for a recruiter or hiring manager.

Focus on summarizing your impact and highlighting key skills and experience. If you’re not sure where to start, look at job descriptions. Usually, somewhere at the top, there is a paragraph summarizing their ideal candidate. Use similar language to describe yourself.

For example: “Data Analyst with a track record of uncovering insights that increased sales conversion, reduced false leads, optimizes marketing spend, and solves complex business problems. Over X years of experience partnering with [business function] leaders and leading cross-functional teams to make data-informed decisions through testing and experimentation, predictive modeling, and tracking success metrics.”

Also use this space to

Mention the technical tools that you are comfortable using
Summarize any relevant parts of your experience and education
Highlight what type of work you are most interested in
Provide examples of problems that you’ve solved with data

Summary or Bio at the top of your Resume

Similar to LinkedIn, at the top of your resume, you can provide a quick snapshot of who you are. However, a lot of folks put a lot of fluff in their summary statement/introduction and then it just becomes wasted space. Many folks recommend omitting a summary altogether and just listing your experience and education.

If you do include a summary:

Keep it short. Aim for 50–75 words, tops.
Make it impactful and specific. Focus on the value you bring, not just your skills.
Don’t say you’re “looking to develop my skills in…” or “looking to gain experience in X industry.” This makes you sound inexperienced. They care about the experience you already have, not the experience you are seeking.
Leave out any fluff. Everyone claims to be detail oriented and have great communication skills. Show, don’t tell, by having a great resume with specific details that communicate how well-qualified you are.

Example:

Accomplished Data Scientist with over X years of experience partnering with [business area] leaders to make data-informed decisions. With a [relevant degree] and proficiency in [technical and quantitative skills], I have a proven track record of leading cross-functional teams to uncover insights that [examples of how I’ve impacted the business].

Your summary statement should be specific to you. It shouldn’t be generic enough that another person applying for the same role could write the same thing. Rewrite it until it is unique to you.

Job Descriptions

First and foremost, focus on selling yourself as the best candidate for the job you want, not the job you have. This is especially important if you are trying to pivot careers.

Leave off experience that is not relevant to the jobs you are applying for. Emphasize the experience that is relevant and demonstrates that you have the necessary skills employers are looking for.

How do you know what’s relevant and necessary? Consult the job descriptions that companies post for open roles. Make a note of what shows up the most in the requirements, and make sure you have examples showing that you meet those requirements, and use the same language they use.

Additionally, when writing about your experience, tell us what you accomplished, not just what you did.

A lot of folks write their job descriptions like a task list. Hiring managers don’t care so much about what you did, they care about how you impacted the business. How your work brought value. So focus on the value.

For example, you could say:

Analyzed hypothesis tests for XYZ business unit and shared best practices for experimentation.

Or you could say:

Increased search-to-order conversion by 5% and annual revenue by $5 million for [business unit] through hypothesis testing and experimentation, including defining success metrics, conducting statistical analyses of results, and identifying methods to improve testing process.

I’ve heard from a lot of folks that they don’t include numbers or outcomes because they don’t know the results. First of all … that’s not going to sound great in an interview, especially if you’re going for a role that is all about quantifying results. If you don’t know, ask the teams you support how they are using your work to make better decisions or achieve success. Not only will that give you information for your resume and future job interviews, but it’ll give you insight into the type of work you do that is most in demand.

However, I know at a lot of companies there is red tape, and maybe you truly can’t get the data on the outcomes. You can use qualitative outcomes (such as “Streamlined the lead generation funnel by analyzing the dropout at each step”) or, using the example above, even without the numbers in the second description, it is an impactful bullet point.

You can also use this format for your personal projects as well as your paid work. For example, regarding a project I did:

Created a recommender system to suggest what to wear for a run based on weather.

Or,

Decreased the number of times I was too hot or too cold when running in the winter by creating a recommender system using KNN to suggest the right outfit based on the current weather.

How many bullet points should you have for each job? A rough guide is 1 for every year you were in that role (round up) plus one extra. I would limit it to around 5–6 bullet points maximum.

Should you list every job you’ve ever had? No. You can leave off jobs that are not relevant to your career goals, or jobs that you held a long time ago that are duplicative of more recent experience. Personally, I have left off jobs that I had over 10–12 years ago.

Education

List all college degrees you have completed as well as any that you started or that are in progress. Add “in progress” or “expected graduation [Year or Month Year]” for in-progress degrees, or “some coursework completed” for unfinished degrees that you don’t plan to complete.

You can also leave off graduation years if you don’t want recruiters and hiring managers to know your age.

Listing relevant courses and projects under your degree can help, but if you don’t have space on your resume, leave them out.

Include any relevant certifications. Note that a certification usually requires a test or assessment of skills, whereas a certificate is given to anyone who took a course. Certifications, when relevant to the job, do hold some weight.

Certificates and non-college courses don’t matter as much. This includes MOOCs (massive online open courses, like Coursera, Udemy, etc). They can certainly help to learn the skills but they don’t carry much if any weight with hiring managers. However, if you don’t have any college degrees, then list them. If you have an unrelated degree, you can list certificates and other courses in addition to the degree.

Projects

You can list projects on your resume, including ones you did for coursework, capstones, and personal projects that you only did for yourself. Summarize them like you would a job description. However, if you have relevant work experience, it’s probably not necessary to list personal projects. Major academic projects are fine to leave in the Education section.

Not sure how to do projects? Here is a guide.

Skills

There are a couple of approaches you can take to listing skills on your resume. You can work them into your job and project descriptions — this is the recommended approach. Or, you can list them in a separate section, ideally at the end of your resume. Focus on technical skills, like SQL, Tableau, Python, statistics, etc. Leave off fluff like “organized”, “great communication skills”, “detail oriented”, etc.

LinkedIn also has a section for listing skills, definitely take advantage of that.

Contact Information

At the top of your resume and also your LinkedIn profile, you need to include relevant information:

Name. Some just do first and last. Some might include a middle initial. Some might include a legal first name and nickname. Some might include only the nickname. Do whatever you are comfortable with.
Location. Just city and state is enough. Personally, I would list the nearest major city (if you don’t live in one), assuming you are able to easily commute to that city.
Do not list your address on your resume. (To prevent unconscious biases and also privacy concerns.)
Email (and phone number on your resume).
Relevant links — LinkedIn profile (for your resume), portfolio (I use GitHub), professional website if you have one.
If you are in the US, do not include a photo on your resume. But definitely include a professional-looking photo on your LinkedIn.

How to order your resume

From most to least important.

If you’re able to write an impactful summary/introduction, include that first. If not, omit it.
If you have relevant experience, list that first in reverse-chronological order. (Newest job first.)
Relevant experience can include jobs (and internships) where you did relevant work even if you didn’t have the “right” job title. For example, if you were a Marketing Specialist and did some data analysis on the job, include that, and focus your bullet points on the data-related work you did.
Relevant experience can also include capstones, research, thesis/dissertation.
If you don’t have paid experience or academic experience, then you can also include contributions to open source projects, datathons, hackathons, and volunteer data projects. If you do have paid/academic experience, then I would omit or limit the amount of unpaid/non-academic work that you list on your resume (for the sake of space), but feel free to include on LinkedIn.
If you have no relevant work experience but a relevant degree (and/or relevant certifications), then list that first.
If you have no relevant education or experience, then put projects first. If you don’t have projects — do some.
Put projects above certificates. How you can use your skills is more important.
I don’t recommend putting your list of skills at the top of your resume. To me, that screams “I have no relevant training or experience.” At least list some projects to demonstrate the skills.

Need more help?

I do personal resume and LinkedIn reviews.

Also check out what other folks have to say:

Ex-Google Recruiter Reveals How to Get FAANG Job Offers
This TikTok creator has a lot of good advice regarding LinkedIn profiles.
Tips to Increase the Visibility of your LinkedIn Profile to Recruiters
LinkedIn Tips (YouTube video)

Want more career advice? Follow me on TikTok, Instagram, or LinkedIn, and sign up for my free data career newsletter.