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Even though 95 percent of employers say thatdata science and analytics skills are hard to find,candidates looking for a data scientist job still need to demonstrate their proficiency in core concepts and skills during the job-search process. A data scientist resume is a key element in telling this story.

A good data scientist resume should include awide range of skillsandqualitiesbeyond the fundamentals of data science. Data is intricate, and most likely, your account managers or creative teams wont understand the technical complexities as you do, explained Lauren Hamer, certified professional rsum writer and founder of LaunchPoint Rsum. Thats why hiring managers look for a mix of technical aptitude and communication skills (e.g., can you work with unstructured data, uncover ways to solve business problems, and present your findings to other stakeholders?), when reviewing data scientist resumes.

In this guide, well cover the major steps to creating an effective data scientist resume, as well as delve into some of the things hiring managers look for in data scientists.

How can a data scientist go about showcasing their technicalandcommunication skills in their resume? Usually this is best done within the work history section, Hamer noted.

In addition to presenting examples of your projects and work, the bullet points should mention the teams and stakeholders you worked with, as well as the medium you used to present the findings to others (detailed Excel reports, case studies, Agile project formats, Zoom, kick-off calls, presentation decks, etc.).

For example:

Produced value-added deliverables for R&D and product marketing by mining and analyzing third-party and customer sentiment data to derive significant, tangible, actionable insights.

Collaborated with data engineers and marketing team to implement ETL process, wrote and optimized SQL queries to perform data extraction to fit the analytical requirements.

Designed rich data visualizations and views using combo charts, stacked bar charts, pareto charts, donut charts, geographic map, transforming the data with Tableau and Matplotlib.

Delivered and communicated research results, recommendations, opportunities to non-technical managers and executive teams, via slide show over Zoom.

To further affirm the skill level of a data scientist and their ability to do their job, Hamer sometimes includes a quote or testimonial from a stakeholder or customer. For example:

Laurens ability to see the bigger picture among the weeds helped our team launch a new product in just 3 months-something that wouldnt have been possible without her detailed algorithms and statistical models. -Bob Jones, senior R&D manager, ABC Company

The other most vital sections to include in a data science resume are technical skills and special projects.

Hamer recommends placing your technical skills summary or toolbox in the top-one third of your rsum, right below your profile summary and before your work experience summary. It should list the platforms, programs, and languages youre familiar with. (Bonus points for prioritizing the specific skills highlighted in the job description.)

While you should briefly mention projects in your work history bullets, Hamer explained, they are so important that they deserve their own section labeled special projects or related projects and a more detailed summary that will help draw the readers eye to them. Again, project summaries provide the perfect platform for explaining your approach, mindset, business acumen and the things that separate great data scientists from good ones.

With that in mind, here is a format for describing each project:

An opening summary should include the target job title in the first line, then convey the candidates best value statement or differentiator something unique.

Think back on feedback youve received from mentors, professors, supervisors, and so on. What do they love about you? Do you understand the big picture? Are you their most reliable worker they dont have to worry about? Are you the one most trusted to train new employees? Mention those in your opening summary:

Goal-oriented Data Scientist offering a proven track record of understanding the business underpinnings of a problem, conducting effective analyses and delivering data-driven insights and value that improve decision making and positively impact the top and bottom lines. Highly motivated and insightful professional with exceptional intrapersonal and communication skills and over six years experience in data mining, extraction, analysis, statistical modeling, machine learning and data visualization. Turning data into valuable information is my passion and forte.

The length of your resume doesnt matter quite as much as the content. Also

Match the job description: To capture the attention of automated and human reviewers, make simple modifications/customizations to match the requirements in the job descriptionincluding the hard and soft skills, the organizational culture, industry expertisebefore hitting Send. Even better, use a free tool likeJobscanorRsum Wordedto compare your resume to a specific job description, make changes, add the right keywords, and get past applicant tracking systems.

Provide work samples:Provide a link to samples or aportfoliothat reflect your work and are representative of how you work and communicate with technical and non-technical audiences.

Be sure to include certifications, coursework:You should includetop certifications,as well as coursework and participation inhackathonsandcompetitionsthat demonstrate expertise in must-have technologies and a passion for continuous learning. (In addition, more specialization and skills will allow you topotentiallynegotiate for a higher salary.)

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Data Scientist Resume: Template, and Best Tips for Writing One - Dice Insights