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The Tech-Talk Balance: What Technical Interviewers Expect from Technical Candidates

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Software engineer job candidates are not succeeding at technical interviews. Although candidates are able to answer technical questions, there is a mismatch of what candidates think interviewers assess versus what criteria is used in practice. This mismatch in expectations can cost candidates a job opportunity. To determine what criteria interviewers value, we conducted
mock technical interviews with software engineer candidates at
a university and collected evaluations from interviewers. We
analyzed 70 interview evaluations from 9 software companies.
Using a grounded theory approach, we compared interviewer interpretations of criteria including: performing a problem solving
walkthrough, applying previous experience to problem solving,
and the ability to engaging in conversation beyond writing code.
From these findings, we provide implications on what candidates
can expect to be evaluated on during technical interviews across
companies, which can sometimes vary significantly.

Published in: Engineering
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The Tech-Talk Balance: What Technical Interviewers Expect from Technical Candidates

  1. 1. The Tech-Talk Balance: What Technical Interviewers Expect from Technical Candidates Denae Ford, Titus Barik, Leslie Rand-Pickett, Christopher Parnin@DenaeFord North Carolina State University
  2. 2. 2 Emphasizes data structures & algorithms
  3. 3. 3 …but others emphasize something else Write Code on Paper Know Your Resume Talk Out Loud Don’t Memorize Solutions
  4. 4. 4 Interpersonal Skills Technical Skills
  5. 5. 5 What matters to interviewers? https://cynematography.files.wordpress.com/2013/11/the-internship2.jpg
  6. 6. Research Questions Are there company differences in interview criteria? How do interviewers interpret criteria for software engineer job candidates? 6 RQ1 RQ2
  7. 7. Department Wide Mock Interviews 7 Emailed Department Sponsors https://www.csc.ncsu.edu/corporate_relations/epartners-faqs.php Emailed Computer Science Students
  8. 8. Participants 8 70 Candidate Evaluations 27 Interviewers Undergraduate + Graduate Internships + Full Time Large + Small Companies Tech+ HR
  9. 9. Methodology 9 Candidates 70 Evaluations + Tech+HR Interviewers
  10. 10. Alias Sector Size Evaluations Interviewers C1WEB Internet Search Large 10 4 C2LAW Legal + Risk Large 8 2 C3DAT Data Storage Large 8 2 C4ENG Consulting Large 6 4 C5STS Analytics Small 4 1 C6MKT Marketing Small 15 5 C7OPS Operations Small 12 6 C8INS Insurance Small 4 2 C9FIN Financial Small 3 1 Total 70 27 Mock Interview Companies
  11. 11. Methodology 11 Candidates 70 Evaluations + Tech+HR Interviewers
  12. 12. Criteria Problem Solving Nonverbal Oral/ Verbal Clarity Clear Concrete Examples Enthusiasm Confidence 12
  13. 13. Methodology 14 Grounded Theory Fisher’s Exact + Steel Dwass
  14. 14. Findings
  15. 15. Criteria p1 Post-hoc pairs (p)2 Problem Solving 0.001* C1WEB /C3DAT (0.0159) C1WEB /C7OPS (0.0433) Nonverbal 0.007* C1WEB /C6MKT (0.0057) C1WEB /C2LAW (0.0057) Oral/Verbal Clarity 0.1142 - Clear, Concrete Examples 0.0392* - Enthusiasm 0.0079* C1WEB /C6MKT (0.0250) Confidence 0.0048* C1WEB /C2LAW (0.0356) C1WEB /C3DAT (0.0356) C1WEB /C7OPS (0.0262) RQ1: Are there company differences in interview criteria? Fisher’s Exact Test -> Post Hoc Steel Dwass Analysis 1 Fisher's exact test across companies. α =0.05 2 Post-hoc Steel-Dwass analysis.
  16. 16. Correspondence Analysis 17 Problem Solving -3 -2 -1 0 1 2 3 c1 C1 C2 C3 C4 C5 C6 C7 C8 C9 2 3 4 -3 -2 -1 0 1 2 3 c2 Nonverbal -3 -2 -1 0 1 2 3 c1 C1 C2 C3C4 C5 C6 C7 C8 C9 1 2 3 4 -3 -2 -1 0 1 2 3 c2 Oral/ Verbal Clarity -3 -2 -1 0 1 2 3 c1 C1 C2C3C4 C5 C6 C7 C8 C9 2 34 -3 -2 -1 0 1 2 3 c2 Clear, Concrete Examples -3 -2 -1 0 1 2 3 c1 C1 C2 C3C4 C5 C6 C7 C8 C9 1 2 3 4 -3 -2 -1 0 1 2 3 c2 Enthusiasm -3 -2 -1 0 1 2 3 c1 C1 C2C3C4C5 C6 C7C8C9 2 3 4 -3 -2 -1 0 1 2 3 c2 Confidence -3 -2 -1 0 1 2 3 c1 C1 C2 C3C4 C5 C6C7 C8 C9 1 2 3 4 -3 -2 -1 0 1 2 3 c2
  17. 17. RQ2: How do interviewers interpret criteria for software engineer job candidates? Problem Solving -> Algorithms: When hiring candidates for a job, the top concern is whether candidates have sufficient technical skills through explaining CS Fundamentals. Nonverbal -> Interest: Interviewers noticed when there was poor communication during the interview through eye contact and poise. Oral/Verbal Clarity -> Fluent Speech: When making a first impression, the first words a candidate speaks and their tone are often the most important. Clear, Concrete Examples -> Connected Experiences: Being able to connect previous experiences to coding problems demonstrated the ability to adapt to new environments. Enthusiasm -> Visible Excitement: How a candidate displayed enthusiasm is one measure of interest and engagement in the interview. 18 [Original Criteria] [Interviewer Interpretation]
  18. 18. Takeaways Interviewers care about technical soundness and the ability for candidates to communicate that skill. Most companies have consistent expectations for candidates across industry and size. One style of interview preparation may not work for all companies; some may require specific skills. 19
  19. 19. On the Horizon Record Interviews with biometrics Identify when interviewers followed up with candidates Ask if interviewer would hire candidate Compare across ranked software engineering universities 20
  20. 20. https://cynematography.files.wordpress.com/2013/11/the-internship2.jpg
  21. 21. @DenaeFord Summary We have support for how technical interviews go in SE! Interviewers want technical soundness+communication Most companies have consistent expectations Preparation for company-specific interview makes a difference 22 Paper: http://bit.ly/TechTalkBalance Blog: http://bit.ly/TechTalkBlog
  22. 22. ++
  23. 23. Correspondence Analysis 24

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