Data science is a fast-growing industry with a wide range of opportunities for employment and career growth. Many students and professionals are flocking to data science courses and certificate programs that will give them the skills needed to find a job in an industry of their choice. However, once you are trained in data science and looking for employment in this highly competitive field, a new challenge awaits. You must be prepared for each industry’s unique process for vetting potential candidates to fill their open positions.
Coding interviews focus on programming and problem-solving, allowing prospective employers to test the skills and abilities of their applicants. So, it is essential for every beginner in this field to learn how to ace this crucial part of the interview process. If you are interested in pursuing a career in data science, these tips will help you prepare for the coding interview and other aspects of building your new career!
What is a Coding Interview?
A coding interview is an interview style used by Big Tech companies and other science and technology-based industries. This interview style tests the skills of the interviewee by introducing a technical problem that needs to be solved with critical thinking and data science tools, like coding. Coding interviews also include questions about your background and skills, as well as questions that test your ability to assess and understand programming languages and algorithms, and your basic knowledge of computer science and engineering such as statistical concepts and methods. Coding interviews are used to learn more about whether or not a prospective employee is prepared to take on a job within an industry or company.
Coding interviews may go by different names, depending on the industry, with the requirements, formats, and structures of the interview also differing. These names include the technical interview or the programming interview and can vary based on company and position. For example, the coding interview at Microsoft is commonly known as the “Microsoft Interview” and the company is known for pioneering this interview style for their engineers and programmers. The coding interview for a Data Scientist or Engineer may differ from the technical interview required by a Programmer or Analyst because the questions asked during the interview reflect the type of job that you will be doing and the knowledge that position will require.
5 Tips to Prepare for Coding Interviews
While some interviews for data science jobs are similar to the more traditional one-on-one interviews, many positions have their own procedures around interviewing new candidates. So, when interviewing for a data science job, there are a few tips and tricks that you can use to prepare for the coding interview. The following list includes what you should study, reference, and review before applying for your next opportunity in the data science industry.
1. Research the Company and Position
The first and most important step in preparing for a coding interview is doing in-depth research on the company and the position. You can start by analyzing the company website and the posting for your job, as well as the coding interview process and expectations. Some companies include on their websites a step-by-step outline of what the coding interview entails. But other companies may require that you use a job-search website, like Indeed, to collect information from past applicants and employees about the process. This research can then be used to structure how to prepare and practice for the coding interview.
This is also a good time to reach out to your own personal network via social media or email, to see if you know anyone who has worked at this company or in the same position. This allows you to learn more about the structure of the interview and what the company looks for during the interview process or on the job. Also, consider contacting hiring recruiters and human resources to learn more about the interview process and format at your company of interest.
2. Review Technical Language and Concepts
Once you have a solid understanding of the format and expectations of your coding interview, and the requirements of the company and position, it is important to compile a list of concepts commonly referenced in the interview, company, or job posting. These concepts can include statistical concepts and theories, or even the latest algorithm or machine learning model, any of which may come up in the technical problem that is presented during the interview.
For example, the coding interview for a Data Scientist working in finance, may reference the language of risk and investing, while the Data Analyst’s coding interview may focus on statistical calculations used in prescriptive and predictive analytics. By reviewing technical language and concepts that are relevant to your position and industry, you can feel more confident in communicating your thoughts and responding to any interview questions.
3. Practice Your Programming and Problem Solving
In addition to developing your theoretical knowledge and understanding of the technical language and concepts in your field, it is also important to practice your programming and problem-solving skills. Most data science jobs require prospective employees to use a specific programming language and style of coding such as Python or Java, which is referenced in the job posting. This language also serves as the foundation for how your skills will be tested.
For example, the coding interview may focus on solving a common problem using a specific language, or even testing and finding the problem with someone else’s code. Many times this part of the coding interview is not only testing your knowledge of the programming language but also your critical thinking and problem-solving skills. This is one of the most important steps to practice in a programming environment well in advance of your coding interview.
4. Create a Narrative of Your Skills
Coding interviews focus not only on your ability to demonstrate technical knowledge and skills but also on your ability to create a narrative of your skills. So you should be able to communicate to the interviewer how your past employment and opportunities are applicable to the position. Preparing for the coding interview means identifying how the data science skills on your resume align with the company or career path.
For example, if you are pursuing a position that focuses on leading a team or a project, you can develop a narrative demonstrating your project management skills. If you are new to the data science industry, it is also good to demonstrate your experience by creating a data science portfolio or online platform that showcases your projects and programming abilities.
5. Test Your Abilities with Mock Interviews
The coding interview is often just one of many interviews you will take part in during the hiring process for a data science position. So, it can be useful to test your abilities with mock interviews. Mock interviews re-create the style and structure of the interview day or process and can be as complex as doing one-on-one interviews with a friend, or as simple as practicing technical questions that you found online. By replicating the conditions of the interview, mock interviews can test your capacity to answer questions and complete problem-sets or technical challenges in the amount of time you expect to be allotted.
Regardless of how much you study and prepare for the coding interview, if you can’t complete the questions during the interview itself, you will not be successful. Mock interviews can show you where you need to improve your skills and ease any anxiety about interacting with an interviewer and answering questions. If you have a network that includes former or current employees at this company, it can be useful to ask these individuals to act as mock interviewers for you. However, any friend, relative, or colleague can also assist you in preparing for the coding interview with mock interviews.
Need to Prepare for a Job in Data Science?
If you are interested in breaking into the data science industry, Noble Desktop offers several data science classes and certificate programs that focus on preparing students and professionals for a job in data science. The Data Science Certificate course offers beginner data scientists the most comprehensive overview of how to manage databases and engage in data analysis. This course also provides assistance with the job search process and data science portfolio to aid in finding entry-level jobs in the industry. In addition, the Data Analytics Certificate for more advanced students prioritizes teaching real-world datasets and business problems. Similar to other data science classes, this program also focuses on teaching the skills that you need to stand out from the applicant crowd and find a job in data science or analytics.