Data Scientist Portfolio Website Guide & Tips

What Is a Data Scientist Portfolio?

A Data Scientist portfolio is a collection of projects that showcase your data science skills. Like any professional portfolio, a Data Scientist portfolio should show prospective employers and clients your expertise, experience, skills, and knowledge. A portfolio acts as evidence of your abilities and should include your very best work. What makes a Data Scientist portfolio different from other professional portfolios is the type of work it includes. The skills your portfolio highlights should be primarily data science skills required of a Data Scientist. A strong portfolio will balance code-based and content-based work and showcase the following skills and knowledge:

• Data collection, cleaning, and analysis
• Machine learning
• Artificial intelligence
• Data visualization
• Effective communication with stakeholders
• Reports 
• Python programming

Your portfolio lets people know who you are and what you do. The next section will guide you through building your Data Scientist portfolio so you can showcase your abilities.

How to Build Data Scientist Portfolio Projects

Creating your Data Scientist portfolio starts with outlining your portfolio structure. Most professional data science portfolios are structured as follows: 

1. An introduction of who you are and what you do. 
2. Expand on your introduction with an About section.
3. Display your contact information. 
4. Three or four projects that showcase your best work.

It used to be that portfolios were printed out and copies offered to recruiters during in-person meetings, but today, most portfolios are digital. This is especially true for Data Scientist portfolios. Web-based portfolios allow recruiters to access your work remotely, study it before and after reviewing your job application, and the website serves as evidence that you know how to digitally present data in an engaging way. Creating a website for your portfolio allows you to create an interactive dashboard in place of a static data visualization. You can include data, your findings, and visual elements like charts and graphs together on one page. When creating a website for your data science portfolio, keep the following in mind: 

• Make sure your pages load correctly and quickly on different browsers. 
• Check that your website uses a responsive layout to look good on computers, tablets, and mobile phones. A responsive layout adapts to fit any screen size.
• Make navigation easy for visitors so they do not miss any important information. 
• Choose only a few projects to showcase so you do not overwhelm site visitors.

If you are enrolled in a Data Scientist certificate program or a data science course led by an instructor, you can ask your classmates and instructor for feedback on what pieces to include in your portfolio. You may include hands-on assignments from class, freelance pieces, or projects from internships you have completed. Data science certificate programs that include mentorship and job search assistance provide an excellent opportunity to have your portfolio reviewed by a professional. 

Choosing Data Scientist Portfolio Pieces

When choosing your portfolio content, consider which projects best demonstrate your abilities and qualifications as a Data Scientist. You may wish to assemble a basic portfolio that can be customized when applying to certain jobs. Limit your portfolio to three or four projects so as not to overwhelm those who review it. You will also want to select work you can confidently discuss. Make sure you are prepared to answer questions about the process and results. Conveying the story behind the data is a key skill for Data Scientists. A strong data science portfolio includes a mix of content-based and code-based projects to show your proficiency with programming languages, data visualizations, and more. A mentor or trusted professional can also help you select the strongest pieces to include in your portfolio.

Choosing a Data Scientist Portfolio Website

Now that you know what you want to include in your Data Scientist portfolio, it’s time to decide where you will host it. Most Data Scientists choose to host their digital portfolio on a website. Using a template-based website builder such as WordPress or Squarespace makes it easy to create a professional layout without needing to code, though some website builders require a paid plan after you have passed the free trial period. WordPress lets you build your website for free, though you must purchase a domain if you wish to remove “wordpress.com” from the name. WordPress, Squarespace, and other website builders offer standard templates designed with portfolios in mind. That said, a data science portfolio differs from a fully visual portfolio like that of a photographer or artist, so you may wish to customize the layout to best display your projects. WordPress is also a good option for those who may wish to start with a template, but maintain the ability to inject custom coding should they choose to do so.

Building a Data Scientist Portfolio Website

To create a professional data science portfolio website, keep the following in mind: 

• Make your layout visually appealing and easy to navigate
• Do not overwhelm your site with too much content as this will be confusing to visitors and can slow down your website’s loading time
• Have a clear navigation menu
• Proof your copy to make it as clear and concise as possible. Also, proof to prevent any typos or other errors. 
• When writing copy for your website, keep SEO best practices in mind.
• Include an About Me section detailing your resume, testimonials, awards, and contact information. 

Polishing a Data Scientist Portfolio Website

Before publishing your portfolio or sending it to prospective clients and employers, review your portfolio one more time. When polishing your Data Scientist portfolio website, keep the following tips in mind: 

• Include three or four strong projects rather than several less impressive ones. Too many projects can overwhelm your website visitors.
• Have a mentor or other professional review your portfolio and offer constructive criticism.
• Check your website’s load times with a free tool like PageSpeed Insights. 
• Review your site on different devices, such as a computer and mobile phone, to verify your site’s responsive layout and ensure your portfolio looks good on any screen size. 

Learn the Skills to Become a Data Scientist at Noble Desktop

If you are looking to start a new career in data science, you might think the only way for you to become a Data Scientist is by enrolling in a four-year university or pursuing other costly and lengthy educational options. However, there are many alternative methods available to help you transition into a data science career, including data science bootcamps and certificate courses designed to help working professionals gain the skills needed to obtain an entry-level job as a Data Scientist. Exploring in-person and live online data science bootcamps and certificate programs can help you find the class that meets your career goals, budget, and schedule. The first step to finding the class that fits your needs is to understand the differences between in-person classes and live online classes. 

In-person data science classes meet in a traditional classroom setting at a physical location. In-person classes have the advantage of providing all necessary equipment, such as computers and software, and allowing students to network with local professionals such as your classmates and instructor. You also have the advantage of learning from an expert instructor face-to-face. The primary drawback to in-person courses is the extra time and money required to commute to the physical learning location. Live online data science classes offer many of the same benefits as in-person classes, including the ability to learn in real-time from an expert instructor. You can also collaborate with classmates, and you have the advantage of learning remotely. 

Noble Desktop offers several different in-person and live online data science classes that can help you start a career as a Data Scientist. The Python for Data Science Bootcamp teaches students foundational programming concepts and how to handle different data types, use conditional statements to control the flow of a program, use Scikit-Learn, Matplotlib, Numpy, Pandas, and other Python libraries and tools. Noble’s Data Science Certificate program and Data Analytics Certificate program provide a deep dive into the topics and skills essential to launching a career in data science or data analytics and offer one-on-one mentorship and job search assistance. All Noble Desktop classes provide students with hands-on experience, flexible financing options, setup assistance, a free retake, small class sizes, and real-time guidance from an expert instructor.

Learn more about Noble Desktop’s in-person and live online data science classes.

You can also learn more about data science careers and data science learning options with Noble’s free Data Science Learning Hub.