what is a data scientist?
More than ever, companies, governments and other institutions rely on data to make their decisions. This data can track everything from traffic flows to consumer purchasing habits to weather patterns. But raw data doesn't help decision-makers choose the best options; someone has to process and analyze it. This task falls to data scientists, who are expert analysts with deep knowledge of technology and statistics.
Data scientists combine these analytical skills with knowledge of the topic they're analyzing to create models based on the data they study. Using these models, data scientists attempt to understand past and present situations and even predict future behavior.
Like all scientists, data scientists not only carry out their analysis but also present their findings to others. Whether that means communicating with corporate management, the government or the public, a data scientist must provide clear, useful information. This means that communication skills are a vital part of a data scientist's job.
Would working in the tech or IT industry as a data scientist suit your analytical mind and knowledge of statistics? Then read on to find out what competencies and qualifications you need to thrive in a data scientist role.
data scientist jobs near youaverage data scientist salary
As a data scientist, you are a highly skilled professional, and your compensation reflects that fact. The median salary of a data scientist was $100,910 in May of 2021. However, because data scientists work in a wide range of different institutions, salaries can vary depending on area of specialization and your employer.
Would you like to know how much a data scientist earns? Where the highest salaries are paid to a data scientist? Then check out this salary page and find out all about the salary of a data scientist in the USA.
types of data scientists
Within the world of data science, you can pursue a number of different specializations. These might include:
- data engineering: A data engineer builds and maintains the frameworks used for analysis by consolidating, cleansing and structuring data collected from multiple sources.
- database management and architecture: A step up from a data engineer, this type of specialist is responsible for actually designing the digital framework of a specific organization.
- operations data analysis: Less technical than other data scientists, an operations data analyst uses statistical software to evaluate and solve business-specific problems.
- marketing data analysis: Using analytic tools, a marketing data analyst is specifically concerned with measuring and improving the effectiveness of a marketing campaign, particularly in terms of ROI and with consideration of marketing trends.
- machine learning: A growing field within data science, data scientists who specialize in machine learning create algorithms that work without direct human participation. These automated systems can work many times faster than humans, making them ideal for dealing with large data sets.
- artificial intelligence: Artificial intelligence (AI) is another specialist area within data science. Although related to machine learning, AI has its own methods and principles, and many data scientists specialize in one or the other.
working as a data scientist
If you're interested in finding out what a job as a data scientist involves, read on. You'll find out about the daily work of a data scientist as well as your work environment and prospects.
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data scientist job description
In this complex information world, companies must deal with an immense amount of information that comes from multiple sources. The information can also have a wide variety of meanings. Making sense of this data as it relates to the functioning of an enterprise is a challenging task. How this data is viewed can have a profound impact on the decisions a business makes and the ultimate outcome and success of that company.
Grappling with this information is precisely what a data scientist does. The role of a data scientist is to take a complex set of information and transform that data into a form that guides a company in making wise actionable choices in solving complicated problems. These problems affect not only that organization but other entities that also must respond to the same or similar issues.
As a data scientist, you use your knowledge of math, statistics and analytical methods to understand data sets. Your work includes:
- identifying patterns within data to spot corresponding patterns in the real world
- building models and algorithms that can use data to help predict future outcomes
- formulating research questions to answer using data
- refining data sets using machine learning and other tools
- communicating your findings to corporate management, political leaders or the public
To accomplish these tasks, you are always learning. Your ongoing education includes keeping up with the latest advances in the field of data science. It also means staying abreast of new developments in software. From data analysis to data visualization, data science uses digital tools. Mastery of these tools is a vital part of your skill set.
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data scientist work environment
As a data scientist, you typically work in an office environment. You will complete most of your analysis using computers and other information technology. Your job may involve some travel to meetings or conferences, but regular travel is uncommon. You may not even work in a traditional office. Increasingly, many data scientists work remotely, either going into an office occasionally or working entirely online.
A data scientist's work environment may also vary considerably from company to company as not all office cultures are alike. It is important to research the companies you are applying to see if your potential employer’s office culture and company values align with your personality.
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who are your colleagues?
Depending on your employer and the industry you work in, your colleagues might include engineers, economists and civil servants. You might also work in close proximity to computer programmers and database administrators. Other specialists you may work with include, but are not limited to, research scientists, market research executives, technical writers and financial analysts.
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work schedule
The work schedule of a data scientist is relatively predictable. You can expect to work a full 40-hour work week, typically on a schedule of 8 a.m. to 4:00 p.m., 9 a.m. to 5 p.m. or some variation of such hours. The good news, however, is that flexibility in hours is typical in many positions.
Late hours or weekend work may come up, but they are rare occurrences. You may need to put in late hours when there are tight deadlines on documents or when you are working on a large project, for example.
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job outlook for data scientists
Your career as a data scientist offers excellent prospects for advancement. In addition to going deeper into data science through experience and even postgraduate study, you can move into other fields. You could specialize in an area of data science, such as artificial intelligence or machine learning. If you enjoy working with large teams of data scientists, consider moving into a management or project management role. If you're more focused on the science side of your work, consider a move into academia as a researcher or lecturer.
In terms of market growth, the U.S. Bureau of Labor Statistics estimates that demand for data scientists will increase 36% between 2021 and 2031. That is a significant rate of growth compared to other occupations, so opportunities for future mobility are high.
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benefits of working for randstad as a data scientist
Working through Randstad offers you a range of benefits:
- being paid weekly
- flexibility
- always a contact person you can fall back on and ask for help from
- many training opportunities
- a range of jobs in your area
Want a permanent contract? But you wonder why it would be interesting for you to work with a staffing company? A temporary job as a data scientist is often a stepping stone to an attractive permanent job. Every year, thousands of people earn a permanent contract with great employers thanks to a temporary job found through Randstad. What's more, many companies recruit their permanent employees through Randstad too!
data scientist skills and education
Degrees adjacent to the field of data science include, but are not limited to, computer science, engineering, physics, and, of course, mathematics. However, even degrees in fields such as economics and psychology can lead to a career in data science, as these areas of study often rely on statistical models.
The majority of data scientists enter the field with a college degree. Most data scientists have, at minimum, a bachelor’s degree, but some of the highest-paying data science jobs require a master’s degree or doctoral degree. Because data science heavily relies on algorithms, deep analytical thinking and work with complex systems and statistics, hopeful data scientists should be well-learned in the various STEM fields.
That said, not holding a degree in STEM does not bar you from pursuing a career in data science. Because the demand for data science jobs is projected to greatly increase for the foreseeable future, there are opportunities for those without the credentials to set themselves on a path toward a data science career. These opportunities include certifications and “boot camp” courses from accredited universities.
An apprenticeship, combining classroom learning with workplace training, can also lead to a job in the field.
skills and competencies
As a data scientist, you will need an abundance of both quantitative and communicative skills. Due to the scope and nature of the work, a data scientist is almost like a jack-of-all-trades within the tech/marketing industry. Here are just some of the skills and competencies you should have as a data scientist:
- strong analytical skills: Data scientists must be able to analyze large amounts of data and draw insights from it.
- programming skills: This field requires working knowledge of various computer programming languages.
- statistical knowledge: Data scientists need a strong understanding of statistical methods and how to apply them to analyze data.
- data visualization skills: Those in this field must be able to create clear and concise visualizations to communicate their findings effectively.
- communication skills: These professionals should be able to clearly communicate their findings to both technical and non-technical colleagues.
- creativity: Good data scientists are always exploring new ways to solve problems.
- time management skills: Those working in this area should demonstrate the ability to manage their time and prioritize tasks effectively.
- teamwork and collaboration: Data scientists must work closely with other teams, such as business stakeholders and IT professionals, to ensure that their work aligns with the goals of the organization.
There is more to being a data scientist than simply analyzing data and constructing models! You will need a plethora of skills and be willing to be a team player!
FAQs about working as a data scientist
Here you will find answers to the most frequently asked questions about data scientists.
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Is being a data scientist a good career?
On top of being one of the fastest-growing, in-demand careers in the USA (demand for data scientists is expected to grow as much as 36% through 2031), data scientists report high levels of job satisfaction. Data science ranks #6 among the best tech jobs, #11 among the best STEM jobs and #22 in the top 100 best jobs! The typically high pay and predictable yet flexible hours no doubt help contribute to the sentiment.
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is being a data scientist a difficult job?
Data science is a rewarding and fulfilling career for those with a strong analytical mind and a passion for math, statistics and problem-solving. As a data scientist, your expert knowledge, models and data sets help important corporations or government leaders make big decisions. It is a rewarding and fulfilling job, but it also means you have to put in the work.
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do data scientists make a good income?
Data scientists are highly skilled professionals and they are in high demand. Their handsome salaries reflect that fact. As recently as May of 2021, the average annual income of a data scientist was $100,910. Of course, the specific area of data science you work in as well as where you stand on the ladder (i.e. entry-level, mid-senior level, senior level) will have a great impact on your specific pay.
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what skills do I need to be a data scientist?
A data scientist must have a strong background in math, physics, engineering and statistics. Familiarity with various programming languages is also a must. But aside from educational and intellectual skills, data scientists should also have a fair range of interpersonal and social skills. After all, you will most likely be working with people in related fields, such as physics and engineering or even business analysis.
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will data science be a good job in the future?
Absolutely. There is a reason the field of data science is projected to grow significantly over the next decade. As the world’s population continues to grow and new technologies develop at break-neck speed, data scientists will continue to be an indispensable asset.
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how do I find a job as a data scientist?
Applying for a data scientist is easy: create a Randstad profile and search our data scientist jobs for vacancies in your area. Then simply send us your CV. If you do not have a resume, no worries. Just check out our resume builder. This state-of-the-art tool will help you to create your own resume. Need help with your application? Check out all our job-hunting tips!
