Top Data Science Skills to Boost Your Resume

The data science industry is constantly changing, with new tools and training being added to the field as the study of information and data develops. It is important to keep updating your skills as well as showcasing those skills through your resume and online profiles. There are several areas of data science that have gained popularity, not only within the public sphere but within job postings and employment opportunities. If you learn to leverage these in-demand skills and communicate them through keywords, you can build a resume that stands out from the crowd and appeals to prospective employers and collaborators!

Using Keywords to Boost Your Resume

As the process of job searching moves to the online realm, it is more common for job-seekers to utilize platforms such as Indeed and LinkedIn to find new employment opportunities and to display their talents for companies and recruiters. In addition, applying to jobs online usually requires submitting a resume and/or cover letter into an applicant tracking software (ATS) system or platform. Each of these platforms is built on algorithms that search through a resume in order to find the keywords, phrases, and skills that an employer wants to see from a prospective employee. Even if an applicant is a good fit for a job, lacking the right keywords or skills in the job materials can result in their application being eliminated by these initial filtering systems before they ever make it to the interview stage.

It is important that data science students and professionals include the top keywords and search items that employers are looking for when crafting job materials, such as a resume. Looking at websites like Indeed and ZipRecruiter, there are a variety of skills that data science students and professionals should ensure are featured in any job materials that they post or submit online. Most of the popular keywords in data science are focused on hot topics in the field, such as the current investment in big data and automation, so the following list includes multiple examples of how to feature these skills on your data science resume.

Top 7 Data Science Skills to Have On Your Resume

1. Algorithms and Artificial Intelligence (AI)

The ability to design algorithms and work with artificial intelligence (AI) and deep learning is one of the most commonly discussed skills when it comes to the future of data science. Algorithms are formulas or processes which can be used to complete tasks and solve problems within a dataset. Pairing algorithms with AI displays knowledge and understanding of how to program or automate a computer or machine to make the process of compiling, sorting, and extracting information from data simpler and more efficient. It is especially important to include keywords of specific algorithms, such as decision trees or artificial neural networks, as well as projects or models which display these skills on your resume.

2. Machine Learning and Model Deployment

Advanced knowledge in designing algorithms and AI go hand in hand with developing skills in machine learning and the deployment of machine learning models for automation and completing complex tasks. Machine learning is also used within predictive analytics and data forecasting, so any project(s), course(s), or certification(s) should be featured within your resume. In addition to including the keywords “machine learning” to your resume, these skills can also be featured by referencing any experience with machine learning tools or software, such as TensorFlow or Microsoft Azure.

3. Python and Programming Languages

Known as one of the most popular coding languages within multiple fields and industries, Python is an open-source programming language that is especially useful for data scientists and developers. When featuring your knowledge of Python on a resume, it is not only important to reference any certifications or coursework that you have taken in the language, but also any additional knowledge of Python libraries and packages which are used for data science, such as NumPy or Pandas.

4. Data Analytics and Statistics

While data scientists can come from a variety of backgrounds and experiences, many of the employment opportunities within the field privilege a firm knowledge of mathematics and statistics. The ability to work with statistical models, equations, and other forms of data analytics. any specialization in these areas should be prioritized on the resume, with a focus on how you have used statistical analysis in order to extract key insights from a dataset. This knowledge of data analytics and statistics can also be displayed through listing training or experience with software such as Microsoft Excel, SPSS, or Stata.

5. SQL and Database Design

Big data analytics prioritizes an understanding of how to organize and search large stores of data. One of the primary skills for data scientists that are interested in these methods is training in the SQL programming language and database design. In addition to being a highly ranked skill for careers in data science, knowledge of the SQL programming language and software is also useful for students and professionals that are interested in pursuing a career in cybersecurity and systems administration. Including keywords such as “querying” should also be included in the resume to display your SQL and database design skills.

6. Data Visualization and Storytelling

As more industries outside of the traditional science and technology fields begin to look for data scientists, it is important for data science professionals to know how to communicate their findings to non-data science audiences. This could be as simple as including keywords like data visualization and data storytelling to your resume, or links to a portfolio of your projects. It is also important to include any training or experience with data visualization tools and software, such as business intelligence (BI) platforms or programs like Tableau.

7. Data Types and Formats

In the era of big data, it is important to include keywords or statements in your resume which indicate that you have some knowledge of different types of data and formats. This can be displayed by making reference to the different sizes, volumes, or scales of the datasets that you have worked with and/or a discussion of the data formats with which you are most familiar. The inclusion of different data types and formats also demonstrates your versatility and ability to tackle projects of different sizes and levels of complexity.

Want to learn more Data Science Skills?

Due to the speed of growth and development in the data science industry, it is important to not only update your resume but to continue learning and updating your skills. Noble Desktop offers a series of data science classes geared towards students and professionals alike that want to keep up to date on the latest data science trends. Whether you are interested in learning more about machine learning algorithms or specializing in Python, there is a data science class for you!

The Python Data Science and Machine Learning Bootcamp combines instruction in programming and predictive models to help expand the skills of students across experience levels. The Python Machine Learning Bootcamp offers more advanced students insight and instruction to algorithms and recommendation systems in order to develop skills that are used within the technology and finance industries. No matter what course you choose, these bootcamps and workshops will ensure that you develop the knowledge and skills that prospective employers are looking for at this time.