You made it! You have earned your qualifications in data science and analytics, compiled your resume, built your professional portfolio projects, searched and applied for jobs with engaging cover letters, and you’ve finally got your first interview lined up!
Here’s 5 interview questions you must-know how to answer before you walk into that interview:
1. What inspired you get into data science / start your data science career?
Why they would ask this: the rise of the data economy and the global skills shortage has attracted many new professionals wanting to break into the data science industry. This is a personality question. They want to determine your motivations for entering the industry and if your philosophies about data science resonate with theirs.
How to prepare: to prove that you are passionate and possess the right mindset for this role – examine their business ideologies but also: remind yourself why you wanted to get into data science in the first place, and evaluate everything you’ve learned about the industry and yourself through out your career journey so far. You will then know why you stayed on your path to become a data scientist and you will be able to answer this question with ease and confidence.
2. Why do you want to work at this company as a data scientist?
Why they would ask this: to determine if you’re interested in solving their particular business problems or if you’re just looking for any data science job.
How to prepare: make sure you research the company, its projects, value proposition and recent developments to answer this question with integrity, and demonstrate to the employer that you understand how your skills will help solve their business problems, that you are excited to be there, and that you respect the opportunity to interview with them.
3. What tools or techniques allow you to work more efficiently / help you successfully complete your data science assignments?
Why they would ask this: to determine which data science tools and techniques you use regularly, are confident using in a professional setting, and if your skills match up with their needs. This is also a fact checking question.
How to prepare: demonstrate that you can identify and apply the most efficient tools and techniques for different data science tasks. Give examples of projects / student assignments / case studies, and how you determined which tools/techniques/processes to use and the outcomes.
4. How has your previous work experience prepared you for this role in data science?
Why they would ask this: to determine your technical proficiencies, soft skills, ability to concisely explain key points, learn about what kind of employee you could be based on your interests, what you took away from your previous roles and if they match the current and future job requirements.
How to prepare: know your resume, projects, and work experience back to front! Be sure to remember key points / project and contract durations, and be ready to explain how your previous work experience (paid, unpaid, related, unrelated) has taught you practical and soft skills that are applicable to this particular position. Be succinct and selective in your response. Explain the context of the roles and what you accomplished / achieved.
5. Tell me about your project(s), your process and the results?
Why they would ask this: to determine if you did in fact create this project, how interested you are in finding data driven solutions. Also if you are familiar with industry standards for project work and management, and to evaluate your explanation of ideas to and communication skills.
How to prepare: go over why you picked that particular data set / website / mobile app etc. to base your data science project on. Be clear on what inspired you, what technologies and processes you used and why. Be explicit about whether it is all your own work or if you worked in a team. Highlight the aspects of the project you enjoyed the most, and discuss what you learned through the experience.
You will then be asked a series of skills based questions.
Why they would ask these questions: These questions and any skills based interview questions – are targeted and designed to reveal your ability to think, cope, and communicate under pressure. It is also used to highlight your practical knowledge, skill level, and your ability to explain complex ideas simply and accurately in the context of the role.
How to prepare: The best thing about this is, you have just completed an intensive learning program that has prepared you for this exact situation. However, it is crucial that you practice your technical skill set before the interview – as it’s much easier to explain a method, if you’ve recently carried out the process.
Your answers to these questions are your opportunity to prove to this employer that you possess the data science, analytics, machine learning, project management, and communicative skill set – they need.
This is the real key, you need to convince them that you are the answer to their skills gap. If you’ve been trained through a practical industry training program, such as Black Cat Data, you will have the skills to fulfil the role.
Graduating with Black Cat Data provides you with more than just an industry recognised and sought after Data Science and Analytics qualification.
BCD Graduates also benefit from: one-on-one job outcomes support, pre-interview training and preparation before being introduced to an industry employer network. Graduates receive resume/LinkedIn reviews, guidance for framing your resume, online branding to fit the needs of employers, ongoing career advice and online and in-person networking opportunities. It’s a real advantage to attend exclusive hiring events to access the hidden job market to land new and exciting career opportunities.
Interested to know the stats? Black Cat Data’s Job outcomes success rate for graduates with a Data Science Level 1 Certification is as follows:
- 90% of BCD Graduates = Job outcome success in 90 days
- 94% of BCD Graduates = Job outcomes success in 180 days
Interested to read some success stories?
BCD works with you once you’ve become trained in data science and analytics to help land your first big data job and direct your career on a path full of job prospects, increased earning potential, and career longevity.