If you’ve decided to pursue a career in development, you’re probably wondering what the next steps are. What’s the best path to take? With all the different types of coding jobs available, how do you know which one is right for you?

Well, it depends. If you’re artistic, you could combine your creativity with your programming skills to create beautiful websites. Or maybe you’d rather work with data — helping companies analyze it for actionable insights or helping users keep their sensitive information safe from prying eyes.

As you’ll learn in the paragraphs below, there are many different types of coding jobs. To help you figure out which one is best for you, we’ll explore 6 of the most popular coding jobs and their responsibilities. Then, we’ll show you where to get started.

1. Front-End Engineer

Front-End Engineers create and manage everything that you see and interact with on a website. Think about the text you’re reading right now, all the menus, and even the cool progress bar that tells you how far along you are in this article. All of this was created by a Front-End Engineer. Front-End Engineers create the world you see on the web page, from the login screen to the layout of your search results.

Average salary: $105,800 with $2,500 annual cash bonus

What makes a good Front-End Engineer?

The most successful Front-End Engineers have a solid understanding of HTML, CSS, and JavaScript. In other words, they’re most familiar with the languages used to create the front end of web and mobile applications. And while Front-End Engineers aren’t expected to have full-depth skills in web and graphic design, it certainly doesn’t hurt to have a bit of a creative touch.

2. Back-End Engineer

Everyone loves working with slick, well-designed apps and web pages, but what good are they if they don’t give you the information you need? That’s where Back-End Engineers come in.

Most apps and websites store their information in large databases on remote servers to be easily accessed later. Back-End Engineers manage these “behind-the-screens” parts of a website. So, when you search for something like “learn SQL” (which we recommend for Back-End Engineers), it’s thanks to them that the results you see are relevant to your search. Similarly, when you’re browsing, it’s the work of Back-End Engineers that allows you to quickly view the most current content available.

Average salary: $120,700 with $4,000 annual cash bonus

What makes a good Back-End Engineer?

Back-End Engineers love solving tricky technical problems. Compared to front-end engineering, which focuses on aesthetics and an engaging experience, back-end engineering rewards the most logical and efficient solutions. Back-End Engineers work a lot with databases using tools like JavaScript, SQL, and Node.js. They also understand the fundamentals of good database creation, management, and data retrieval.

3. Full-Stack Engineer

What if you love both the creativity of front-end engineering and the technical challenges of back-end engineering? Then, consider becoming a Full-Stack Engineer.

While most people think of a Full-Stack Engineer as a Front-End and Back-End Engineer combined, the truth is they’re much more than that. Full-Stack Engineers also understand how front end and back end components interact and communicate with each other.

Average salary: $107,300 with $4,100 annual cash bonus

What makes a good Full-Stack Engineer?

As you might imagine, Full-Stack Engineers have an appreciation for all parts of the development process, from building engaging user interfaces to creating efficient database structures. They’ll also be familiar with the languages used for front-end and back-end development, including HTML, CSS, JavaScript, Node.js, and SQL.

4. Data Scientist

Data science is booming as people and businesses have more and more access to data. The wealth of data we create daily is too much to analyze with traditional methods, so companies rely on data professionals to make sense of it all. Enter the Data Scientist.

Businesses need people who have both the programming skills to automate data analysis and specific field expertise to make sense of what the data and results mean. In other words, companies need more Data Scientists.

Think of data science as a broad field with many potential niches. For example, it’s Data Scientists who develop systems that recommend playlists on streaming platforms like Spotify and YouTube. It can also be used to build machine learning models.

Average salary: $119,400

What makes a good Data Scientist?

If you’re switching to development after years of working in another field, you might wonder whether all that knowledge and experience will go to waste. The answer is that it doesn’t have to! Data Scientists are experts in multiple fields, namely statistics, computer science, coding (including R and Python), and specific fields of expertise. So, if you’re a new developer with past experience in another field, then you’re already well on your way to becoming a great Data Scientist.

5. Data Analyst

How does a company figure out which products are the most popular? What about the most profitable? When adding new products, how do you know if they’ll appeal to your customers? And what is it about your business that makes people choose your services over someone else’s?

Believe it or not, most businesses have enough data at their disposal to answer these kinds of questions. It’s up to Data Analysts to work with multiple data sources to find their answers.

While Data Analysts and Data Scientists sound similar, they perform different roles. Both help make sense of large data sets, but Data Analysts focus on business performance and what a company can do to improve. In another post, we take a closer look at the difference between Data Scientists and Data Analysts.

Average salary: $70,000 with $2,500 annual cash bonus

What makes a good Data Analyst?

Because Data Analysts specialize in using data to improve business performance, they’re comfortable working both behind the terminal and in the boardroom. Many analysts use SQL and Python to work with large, complex datasets and distill them into clear visuals and summaries that non-technical teams can understand. They’re also great communicators who can explain how the insights gathered from large datasets can contribute to organizational goals.

6. Cybersecurity Specialist

Cybersecurity becomes more and more important every day. No one wants their information to fall into the wrong hands, and Cybersecurity Specialists keep our data safe by preventing attempts to steal or compromise it.

Cybersecurity Specialists monitor, detect, investigate, and respond to risks and vulnerabilities within a company’s network. More and more companies are recognizing that cybersecurity is a necessity rather than a luxury, which means that the demand for qualified cybersecurity professionals is soaring.

Average salary: $57,500 with $5,000 annual cash bonus

What makes a good Cybersecurity Specialist?

Much like Back-End Engineers, Cybersecurity Specialists enjoy solving complex problems using logic. They also adopt a forensic approach to determine the root causes of a system’s weaknesses and vulnerabilities.

Lastly, a good Cybersecurity Specialist knows how to think like a hacker and stays up to date with the latest cyberattack techniques.

Take the next step in your coding career

Hopefully, this list of 6 types of coding jobs helped bring you closer to your dream career. If you can see yourself in any of the roles listed above, check out our Career Paths. Our Career Paths take the guesswork out of figuring out which skills you need to move forward in your journey. We’ll teach you everything you’ll need to know to land an entry-level position in our:

If you’re more interested in keeping data safe from cyber threats, take your first steps into the field with our introduction to cybersecurity course. And if you need some extra support, our community is always there to help.

Many companies have decided to stay remote for the long term. In the United States, around 22% of the American workforce is expected to be working remotely by 2025. This means Zoom interviews will more than likely be a part of the hiring process. To help you prepare, we’ve cultivated this list of 9 tips that’ll help you ace your Zoom interviews.

Practice

Before we delve into the tips, we want to stress the importance of practicing before your interviews. Practice is more important than ever before when interviewing over Zoom because it’s easy to get thrown off your game in what may feel like an unnatural environment. Practicing ahead of time sets your mind at ease, makes it easier to remember important facts and processes, and gives you a chance to come up with an interview strategy.

Practicing for assignments and presentations

In some interviews, particularly those involving software development, coding, or other tech-related skills, you may get an assignment ahead of time. During the interview, you will have to present your solution. It’s important to remember:

1. The way you present your solution is as important as the solution itself. While preparing for your Zoom interview, ensure your thoughts are well-organized and presented in a straightforward, logical manner. Even someone without your depth of technical knowledge should be able to follow along.
2. Practice your entire presentation from beginning to end. Then, hone in on spots where you feel things may not be 100% clear or make you a little nervous. Practice these parts repeatedly until you feel comfortable.
3. While you don’t have to memorize your material, you’ll want to familiarize yourself with it enough to speak directly to your interviewer instead of reading from your notes.
4. You don’t have to look directly into your camera while giving your presentation. Practice looking at the faces of those you’re presenting to. If possible, have a friend join you on Zoom for a practice session. Watch your audience’s faces. If you see a puzzled look, it’s OK to politely say, “Allow me to explain that again but from a different angle.” In this way, your presentation changes dynamically according to your audience’s reaction.

Practicing for whiteboard presentations

With a whiteboard presentation, you should focus on making your solution as clear and thorough as possible. To do this:

• Write down your solution and talk it through. In another we post, we explain why it’s crucial to explain your approach during technical (or whiteboard) interviews.
• Don’t be afraid to ask for clarification. Asking questions gives you time to gather your thoughts and can help you avoid misinterpreting the problem.
• If you’re coding a solution and forget the proper syntax, don’t make something up. Acknowledge that you forgot and put something else where the syntax would go. You’re usually being tested on your problem-solving ability, not your ability to remember syntax.

9 Zoom interview tips to help you land the job

The 9 following tips are pulled from the video below, in which several of our team members with recruiting experience share some tips for performing well during Zoom interviews. Their suggestions range from tips that help you look the part, showcase your thinking abilities, and relax both yourself and the interviewer.

1. Ask questions

Asking questions is one of the best Zoom interview tips for several reasons:

• When you ask questions based on something the interviewer said, it shows you’re actively listening.
• Asking questions gives you time to gather your thoughts.
• The right question can help you avoid critical miscommunications.
• After you ask a question, you can take a deep breath and calm down while the interviewer answers.
• Someone who asks questions comes across as inquisitive, thorough, and thoughtful — all of which are ideal qualities in a job candidate.

2. Dress the part

It’s better to overdress than under-dress. Even though you may be working remotely and your “uniform” may often be your pajamas, you should dress as if you’re going to the office. Ask your interviewer ahead of time about how to dress or look up the company’s dress code. Then, while choosing your outfit, step it up a notch to ensure you come across like a professional.

3. Test the tech

Well beforehand, you should test the various Zoom features that may impact the success of your interview. These include:

• Screen sharing, including optimizing the screen share for video.
• How Zoom works with the bandwidth you have at home or where you’re interviewing. If you have a poor connection, you may want to consider heading to a library or somewhere else with privacy, a relatively quiet ambiance, and sufficient bandwidth.
• Muting, if necessary.
• Using virtual backgrounds, if necessary.

4. Think about lighting

Using good lighting is one of the most important Zoom interview tips. You should ensure your face is lit so you can be clearly seen without unnecessary shadows. You can grab a simple influencer light setup for around $25 online, or you can use lamps on either side of your computer or device. Regardless of your setup, keep the following in mind:

• Position the light in front of your face, not behind or to the side.
• Get rid of or dim competing light sources, such as sunlight, overhead ceiling lights, or lamps.
• Avoid aiming the light in your eyes so you can maintain a natural look during the interview instead of squinting.

5. Turn off notifications

Notifications coming through your phone, laptop, or other devices can throw you off your game. Turn all notifications off. In some cases, you may want to set up automated responses so important contacts don’t think you’re ignoring their calls, texts, or emails.

6. Breathe

Take deep breaths throughout the interview. This gets oxygen to your brain, which helps you think clearer and relax.

7. Talk about something personal

You can still make a personal connection during a Zoom interview. Share some information that fleshes you out as a person. If you’re uncomfortable sharing personal details, you can lightheartedly acknowledge people or pets in adjacent rooms if they make noise. This shows you have a normal life outside of work.

8. Smile!

Smiling relaxes both you and your interviewer. It also makes you look younger and happier, and it’s contagious, often spreading your joy to the person you’re talking to. Smiling also releases endorphins, which can boost your mood and alleviate nervousness.

9. Take notes

Taking notes helps you keep track of important things the interviewer mentions. Then, you can bring them up again later at the end of the interview to illustrate your attentiveness. Note-taking can also make it easier to gather and organize your thoughts in preparation for an answer.

With these Zoom interview tips, you can showcase your knowledge and skills while maintaining your composure. Now that you’re ready to put your best foot forward, the next step is ensuring your skills are up to par.

We have a full catalog of programming courses designed to build and strengthen your knowledge and set you apart from other Zoom interview candidates. With our Career Paths, you can even create a comprehensive portfolio to showcase during your interviews.

Data Scientists are a hot commodity, with U.S. News reporting that there are 10,300 data science jobs available in the United States alone. Despite the wealth of open positions in the field, you’ll still need to ace your interviews to land one.

To help you prepare, we’ll walk you through what you can expect during a Data Scientist interview, some common questions, and tips for answering them. Or, for a more in-depth exploration of a Data Scientist’s fundamental knowledge and skills, check out our Data Scientist Career Path.

What should someone expect when going in to interview for a job as a Data Scientist?

When going in for a Data Scientist interview, you can expect your interviewer to ask questions that test your knowledge of gathering, analyzing, and applying data. Also, because Data Scientists need to produce, examine, and interpret datasets, the interviewer will want to see your problem-solving skills. They might also check on your ability to work with others and maintain a focus on high-level objectives — not just the figures on your screen.

You can also expect them to ask questions about your work history, challenges you’ve faced, and why you want to work at their company. Even though Data Scientists spend a lot of their time working with data, working with people is just as important — so you should expect some questions about your soft skills along with your technical knowledge.

Data Scientist interview questions

Data Scientist interview questions can be grouped into two basic categories: technical or behavioral. Technical questions help the interviewer gauge your familiarity with the tools you’ll need as a Data Scientist. Behavioral questions help illustrate your personal competencies and thought processes. While the technical questions may seem more difficult on the surface, you should take the time to prep for both.

Behavioral Data Scientist interview questions

Again, behavioral interview questions help your interviewer understand who you are as a person. These questions often center around your experience, thought processes, aspirations, and motivations. Here are a few common behavioral Data Scientist interview questions.

Why do you want to be a Data Scientist at this company?

This question gives you the opportunity to talk about:

• Why you enjoy being a Data Scientist
• Specific aspects of the company’s products or services that draw you to it
• Elements of the company culture that you find attractive
• Specific projects the company has been involved with that appeal to you

When answering this question, you’ll want to show that you’ve done your research about the company and what it offers. You should also explain why you’re passionate about data science as a problem-solving tool.

How do you deal with challenges?

To answer this question, you’ll want to show you know:

• How to solve problems involving both data and interpersonal relationships within a team setting
• How to stay calm under pressure
• How to communicate with others on your team when addressing an issue
• How to both lead and follow when a challenge arises

Discussing how you address challenges that arise within a team environment allows you to showcase your ability to listen, communicate effectively, and help yourself and others focus on the team’s objective. While talking about challenges related to gathering, organizing, and analyzing data, you have the chance to show your ability to think creatively and find solutions.

How has your previous experience prepared you for this role?

Data Scientist interview questions like this help your interviewer assess your understanding of the role for which you’re applying, as well as your ability to use your experiences as learning tools. Explain how universal skills like effective communication and collaboration transfer to your new role. You could also highlight any relevant tools or techniques you’ve used in previous positions.

Technical Data Scientist interview questions

Technical interview questions often focus on how you approach the challenges Data Scientists face every day. In some cases, the question itself may not specifically allude to any technical tools, but you should still view your answer as an opportunity to show you know which tools and techniques best solve key problems.

Before the interview, it’s a good idea to mentally list the tools you’ve used to solve problems, ranging from data science-specific tools like SQL and Python to general tools like Excel and PowerPoint.

What is selection bias, and why is it important to avoid it?

Selection bias refers to data samples that aren’t randomly selected. Avoiding selection bias is important because insights derived from biased datasets aren’t useful. While answering this question, discuss the tools and methods you’ve used to avoid selection bias, such as weighting, boosting, and resampling data.

Are large datasets always the best choice?

The best way to answer a question about the ideal size of a dataset is to explain how it depends on the context of the situation. Then, provide examples of how different circumstances require different sizes.

For example, large datasets aren’t always cost-effective because they require vast amounts of computational power, human resources, and time to maintain. Plus, there might even be redundancies in your data. In many situations, you can use a smaller dataset without sacrificing the validity of your results.

What is meant by root cause analysis?

Root causes analysis involves reverse-analyzing an issue to figure out the original problem that caused it. But, your answer to this question shouldn’t stop after you’ve provided a definition. Provide an example of how you used root cause analysis to solve a problem either at a previous job or in your studies.

How do you find outliers in a set of data?

While answering this question, showcase your understanding of outliers by explaining how they jeopardize the integrity of your dataset and can possibly lead to errors in your results. Then, explain how you identify outliers with methods and techniques like composing histograms or using quartiles or standard deviations.

By practicing the technical and behavioral questions above, you’ll be well on your way to landing a position as a Data Scientist. Remember to prepare ahead of time so you’re comfortable and ready to show why you’re the best choice for the job.

If you’re still feeling uncertain and want to ensure you’re well-prepared, check out our Data Scientist Career Path. You’ll learn all you need to know to gain an entry-level position in the field. Plus, you’ll also build a portfolio that showcases your skills to future employers.