The article discusses unconventional lessons learned from empathetic interviewing of Computer Science students applying for data science and engineering internships, focusing on fostering meaningful discussions, ensuring learnings for all applicants, setting clear expectations, and transparent communication.
The interview process involves stages like interview brief, CV vetting, 1-hour interview, and post-interview feedback, aiming to judge potential effectively and create a positive experience.
Tips include starting with guiding questions, avoiding overvaluing correct answers, and using curiosity as the primary lens in technical problem-solving interviews.
The article emphasizes the importance of observing how candidates navigate challenges, connect concepts, and maintain effective communication during interviews.
It highlights the significance of understanding candidates' learning and problem-solving styles through the use of tool-assisted development and explores different prompting styles for effective coding exercises.
Feedback after the interview helps candidates reflect on their performance, learn from the experience, and communicate expectations more clearly.
Effective interviewee behaviors include clear communication, structured reflections, and adaptability, while ineffective behaviors include unstructured responses and neglecting behavioral aspects.
Tips for interviewers include providing written feedback, developing facilitation skills, and remembering the significant impact their feedback could have on candidates' future opportunities.
The article concludes by emphasizing the role of empathetic interviewing in bridging understanding, respecting human potential, and shaping long-term partnerships beyond technical skills.
It encourages both interviewers and interviewees to approach interactions with curiosity, preparation, and reflection to enhance the interview experience.
Finally, it calls for raising the bar in interviewing practices by fostering a culture of kindness, thoughtfulness, and collaboration for meaningful outcomes on both sides of the table.