Do you know the question, at which many good candidates fail during the interview?
Do you have any questions to us?
Picture this: you had an hour interview, where you went through all kind of questions testing your technical knowledge as well as cultural fit. Finally they say: "Do you have any questions to us?". You, smiling because the interview is almost over, answer: "No, no, I don't have any questions". And in one sentence you just did 2 mistakes: missed the opportunity to learn more about the role and the company and created the impression that you don't care much about this role 😣
If you really want this job, come prepared. To help you, I summarized questions in 10 FAQ categories important to the most Data Scientists. You don't need to cover all of them and bombard the interviewer with all type of questions. Find the topics important to you and use the list for inspiration to come up with your own questions.
Bonus points: don't wait till the end of the interview and "Do you have any questions to us?"
Ask your questions during the interview if the topic pops up 😉
Good luck!
Data infrastructure and tools (particularly useful if they mention all cloud providers and buzz words in the job ad) What kind of data infrastructure do you have in place?
Which tools and technologies does your team primarily use for data analysis and machine learning?
What cloud platforms do you use for data storage and processing?
How do you handle data versioning and lineage?
Team structure and collaboration How is the data science team structured?
How do data scientists collaborate with each other?
How are data science projects typically staffed? Do you use a pod structure or assign individual data scientists to projects?
What tools do you use for collaboration and knowledge sharing within the team?
How often does the team meet, and what's the format of these meetings?
Cross-functional interactions with other departments How does the data science team interact with other departments?
How closely does the data science team work with the product development team?
What's the process for collaborating with the business strategy team on new initiatives?
How do you ensure that other departments understand and can effectively use data science outputs?
Project lifecycle and methodologies Can you walk me through a typical data science project lifecycle here? Do you follow any specific methodologies like Agile or Scrum?
How do you prioritize and select data science projects?
What's your approach to model deployment and monitoring?
How do you handle model updates and versioning?
Opportunities for professional development What opportunities are there for continuous learning and skill development?
Does the company support attending conferences or pursuing further education?
Do you have a mentorship program for data scientists?
Is there a budget for online courses or certifications?
How do you encourage knowledge sharing within the team?
Performance assessment How would you describe the characteristics of someone who would succeed in this role?
If I take this position, how would my performance be measured?
What I should achieve in the next 6 months?
How are individual and team goals established? Is it a collaborative process?
Work-life balance and remote work policies What's the typical work schedule like?
What are your policies on remote work or flexible hours?
How does the company support work-life balance during busy periods or project deadlines?
What's your policy on after-hours communication?
Impact of data science on business decisions Can you give an example of how a recent data science project directly impacted business strategy or decision-making?
Can you share an example of a data science project that significantly impacted revenue or reduced costs?
How are data science insights communicated to executive leadership?
What metrics do you use to measure the success of data science projects?
Challenges the data science team is currently facing What are some of the biggest challenges your data science team is currently working to overcome?
Are there any areas where you're looking to improve your data science capabilities?
How do you address challenges related to data quality or availability?
Long-term vision for data science within the company What's the long-term vision for data science within the company?
How do you see the role of data science evolving here over the next few years?
Are there plans to expand the data science team in the near future?
What emerging technologies or methodologies is the company interested in exploring?
How does the company see AI and machine learning shaping its competitive advantage in the coming years?
If your favorite question is missing, feel free to share it in the comments! And good luck at your next interview! 🍀
Bình luận