In today’s digital age, businesses and firms across the world are intricately connected through the internet. Their online activities generate an enormous amount of data at a rapid pace. As a result, firms all over the world are now compelled to deploy analytical as well as statistical methods to achieve quicker data insights. The world's leading research and advisory company, Gartner, estimated that by 2020, the worldwide Business Intelligence (BI) and analytics market would expand to a whopping $22.8 billion.
Any successful organization today, whether a startup or a tech-giant, needs to be data and analytics-driven. By methodically sorting and organizing the vast data, and applying analytics, companies can not increase their market share and may even save millions of dollars annually.
If you’re ready to be a part of this exciting field, we can’t blame you. Data science is a challenging and rewarding career, and the job market continues to grow. If you’ve already got the skills you need to get hired, we’re here to help you through the next step: crafting the perfect data science resume.
What Is Data Science?
According to a PeerPaper Report by ‘IT Central Station’, a leading product review site for enterprise technology, the term “data science” refers to “a collection of practices that leverage computer power to extract knowledge or insights from data.” By identifying patterns, businesses can harness predictive analytics. Data science can enhance the business value of enterprises because it enables them to improve their understanding of operations, sales growth, customer experience, and more.
Data science includes data mining, machine learning, predictive analysis, and other related fields. It’s a multidisciplinary field that combines programming, machine learning, applied mathematics, algorithms, and more.
Data science and machine learning are fundamental to a tech company’s growth, as well as risk and cost reduction. This is thanks to the use of predictive analytics to predict future events. The truth, however, is that the method of implementing predictive analytics can be quite difficult; particularly when it comes to finding the right mix of analysts and data scientists. To achieve success with analytics, the ideal technique lies in an organization’s ability to find out particular business-use areas or issues. Once those strategies are implemented to achieve the objectives, the project will be successful.
Resume Tips for Aspiring Data Scientists
Here are a few of our most useful tips for polishing up that data science resume and getting a call back.
1. Introduce Your Full Range Of Expertise
Keep in mind that the field of data science is still pretty new. Because of this, some employers still need to grasp the full value of it. Mention your responsibilities and accomplishments as a data scientist, and how they impacted the bottom line or helped to improve business operations.
2. Describe Previous Work Experience
Here you can demonstrate, concisely but with sufficient detail, how you leveraged your data analysis skills in previous projects. You’ll also want to discuss your results.
Be specific about your work experiences, and share relevant examples to add to your credibility. Demonstrate the results of your actions in a way that’s easy and quick to understand.
Some examples of a data scientist’s work responsibilities and achievements are as follows.
- "Collected raw data from various websites, then analyzed and interpreted it"
- "Increased overall productivity of the project and reduced unnecessary costs."
- "Maintained and managed the company's Microsoft SQL server."
- "Increased the accuracy of forecasting software from 75% to 90%."
3. Highlight Your Relevant And Unique Skills
As a data scientist, you should be able to demonstrate how proficient you are at managing tools for studying data. You should mention the computer or data processing programs you generally use to work with data science. Also, try and make sure you incorporate a means of highlighting your level of aptitude for the given tool. This will help to better reflect your potential.
It’s also vital to make sure you convince your recruiters that you can handle interpersonal situations as well. So, be sure to list those crucial abilities. This holds particular importance since you are highly likely to communicate with people who aren’t always data scientists. Finally, any additional skills, like foreign language proficiency or online certifications can also make a great impression on the recruiters.
4. Write A Well-Rounded Career Objective
Naturally, you want to make a first impression that’s impactful and long-lasting. With your career objective usually positioned right at the top of the resume, this is your chance, so make it count.
When it comes to the career objective section of technical resumes, lots of people get confused about what to put. While some sources recommend you reserve as much space as possible to elaborate on your technical skills, we advise that you include a comprehensive career objective in your data scientist’s resume.
Your career objective is likely the first thing a hiring manager will notice when they pick up your resume. You can perceive it as an area to mention your relevant experience, skills, and education in a neatly wrapped and easy-to-read introductory package for the hiring manager.
Have a look at the following example of an impeccable data scientist career objective.
“Data scientist with 3+ years of experience in executing data-driven solutions, and implementing them to increase efficiency, accuracy, and utility of internal data processing. Well-experienced at creating data regression models, with the help of predictive data modeling. Also adept at analyzing data mining algorithms to deliver insights and implement applicable solutions to complex business problems. Looking forward to utilizing my Bachelor of Computer Science and Master of Data Science to manage statistical machine learning and data-related solutions in your organization.”
5. Infuse The Professional Experience Section Of Your Resume With Action Verbs
To attract your potential employer, begin each bullet point in the professional experience section of your resume with strong action words. Using solid action words in the beginning is a surefire way to persuade a hiring manager to read the rest of your resume. And this, in turn, will increase your chances of getting called for an interview.
Make use of the following action verbs to maximize your impact:
6. Quantify Your Achievements
While most of your life you’ve been asked to steer clear of jargon, your data scientist resume is a little different. Here’s where you can show off your technical prowess. This is the right place for you to use technical lingo and highlight the accomplishments of your data scientist career.
Adding numbers to the professional experience section of your resume demonstrates that you’re a results-oriented data scientist. It also displays the measurable impact on time, percentages, and costs your actions had on the company.
Keep on Learning
Combined with a killer data science cover letter and great references, these resume tips will help you influence your prospective employers. Whether you’re a new on the scene or a seasoned data scientist, make sure your complete range of hard and soft skills are well reflected in your resume.
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