Interview: behavior

Design

List of questions

Author

Chi Zhang

Published

October 6, 2024

STAR: situation, task, action, result

Highly relevant

Collaboration & Communication

Explain statistical concepts to non-experts; collaborate with cross-functional teams; resolve disagreements

Tailoring technical language, teamwork, conflict resolution, and maintaining professional relationships

Tell me about a time when you had to explain complex statistical concepts to a non-statistical audience (e.g., clinical staff or stakeholders). How did you ensure they understood?

Focus on how you tailor technical language to a non-technical audience.

Case 1: teaching sensitivity, specificity to clinicians

  • S: part of the statistics course, audience are not very familiar with math and probability
  • T: this topic requires linking sens, spec with prevalence to show that rare disease screening with diagnostic tests have many false positives
  • A: instead of looking at the formulae, use visual aids, draw some squares with different color to indicate the change of prevalence, and how a large proportion of positives indicated by a very sensitive test are actually false positives
  • R: students appreciate the visual aids, positive feedback, and good test results

Case 2: teaching randomness and distribution with webR

  • T: illustrate how fixed parameters for a distribution (such as normal) could take slightly different forms, difference of random seed
  • A: make interactive code chunks in class, so students would try it
Describe a situation where you collaborated with a cross-functional team (e.g., clinical researchers, data managers, regulatory staff) to complete a project. How did you ensure effective communication and collaboration?

Focus on your teamwork and adaptability in a multidisciplinary setting.

Case 1: work experience at FHI

  • S: covid times, surveillance, important to deliver reports in a timely manner
  • T: maintain RT surv. system, with a range of people both inside the team (epi, project manager, technical people and web dev) and outside (infectious disease people, intl. network, media)
  • A: we had different strength, I use my R skills to do the package maintenance, and quickly developed skills for shiny websites to support the team
  • R: successful deliverables, improved the efficiency from 5 reports to thousands

Case 2: phd project

  • S:
  • T:
  • A:
  • R:
Have you ever faced a situation where the clinical team (or else) disagreed with your statistical analysis or interpretation of data? (can be any other disagreements such as work style..) How did you handle it?

Emphasize how you navigate differences of opinion, maintain professional relationships, and resolve conflicts.

statistical advising in general, sometimes have to choose different methods

Case 1: Phd AHUS paper

  • S: paper collaborated with clinicians who provided data
  • T: disagreement on how close to look at individual patients
  • A: compromise from both side, do careful analysis in a next paper
  • R: developed an R package to do that

Case 2: Norkost dietary report

  • S:
  • T: need to carry out analysis with data provider
  • A:
  • R:
Can you tell me about a time when you had to meet tight deadlines while ensuring the accuracy of your statistical work? How did you manage it?

Highlight time management, prioritization, and quality control under pressure.

Case 1: PhD dtw paper revision

  • S: Review paper with major corrections
  • T: lots of additional analysis to do
  • A: implement, test fast, send to cluster to run at large scale. all while keeping an eye on the deadline, and leave sufficient time to revise and write
  • R: managed to do it

Problem Solving & Adaptability

Identify and address data or analysis issues; manage incomplete data; adapt to protocol changes

Analytical thinking, attention to detail, flexibility, ensuring study continuation

Describe a time when you identified a potential problem in the data or the statistical analysis plan. How did you address it?

Focus on your problem-solving skills and attention to detail in identifying and rectifying errors.

Case 1: PhD dtw paper revision

  • S:
  • T:
  • A:
  • R:
Important!Have you ever encountered incomplete or inconsistent data during a clinical trial? How did you handle the situation, and what actions did you take to ensure the study’s integrity?

Discuss your approach to data cleaning, imputation, or working with missing data.

  • S:
  • T:
  • A:
  • R:
Tell me about a time when you had to adapt quickly to changes in a clinical trial protocol or unexpected results from an interim analysis (or else). How did you manage the change?

Highlight your adaptability, ability to pivot, and your role in ensuring the study’s continuation.

Case 1: PhD dtw paper revision

  • S:
  • T:
  • A:
  • R:

Ethics & Compliance

Ensure regulatory compliance and handle sensitive data

Knowledge of FDA/EMA/ICH-GCP guidelines, ethical decision-making, data integrity & confidentiality

Tell me about a time when you had to handle sensitive or confidential data. How did you ensure the integrity and confidentiality of the data?

Focus on data security, compliance with protocols (like HIPAA), and maintaining confidentiality.

Generally there is a system in place, such as TSD. So need to refuse the analysis when others breach it

Case: advising project

  • S: clinician sent me very sensitive dataset via email
  • T:
  • A: refused to work on it until it’s properly denonymised
  • R:

Leadership & Initiative

Take initiative to improve processes; lead or mentor team members

Process improvement, leadership, mentoring, aligning team with trial goals

Describe a situation where you ((took the initiative** to improve a process or approach within your work. What was the outcome?

Highlight examples of process improvement, innovation, or contributions to more efficient study designs or analysis methods.

Case: renovating statistical course with R and Quarto

  • S:
  • T:
  • A:
  • R:
Tell me about a time when you had to lead or mentor junior statisticians or team members during a study. How did you ensure they were aligned with the study’s goals and protocols?

Demonstrate your leadership, mentoring, and coaching skills.

Case: noreden

  • S:
  • T:
  • A: set out plan for the r programming part, set up schedule to sit together to work on problems, do quality check in the end; create documentation website for collaboration
  • R:

Dealing with Challenges or Failures

Manage unexpected challenges; learn from mistakes or trial failures

Resilience, critical thinking, learning from setbacks, making informed decisions

Can you tell me about a project that did not go as expected due to statistical issues or challenges? How did you handle the situation and what did you learn from it?

Showcase your resilience, learning from setbacks, and steps taken to mitigate future issues.

Case: phd paper 3 which didn’t go as planned

  • S:
  • T:
  • A: use time in a better way, pivot to something else
  • R: lesson learned: better planning would be ideal; find things to do;
Important!Describe a time when you had to make a difficult decision during a study, such as adjusting the analysis approach or advising the study to stop early based on statistical results. What was the outcome?

Focus on your critical thinking, ethical decision-making, and impact on trial success.

Case: phd paper 3 which didn’t go as planned

  • S:
  • T:
  • A:
  • R:

Attention to Detail & Accuracy

Identify and correct errors; ensure precision in statistical work

Meticulousness, responsibility, focus on ensuring trial success through accuracy

Tell me about a situation where you caught a mistake in your own statistical work or in that of a colleague. How did you handle it and what was the result?

Highlight your meticulous attention to detail and responsibility in ensuring data accuracy.

Case: COVITA study, table making

  • S:
  • T: review the paper before submission
  • A: tell the first author that it’s crucial to change it
  • R:

Case: CB study, PCA analysis

  • S:
  • T: reproduce the analysis made by someone else, unable to do so
  • A: tell the first author that they need to revise
  • R:
Describe a time when your attention to detail significantly impacted the success or outcome of a study. What was at stake, and how did your actions make a difference?

Emphasize the importance of precision in statistical analysis and its effect on trial outcomes.

Case: COVITA study, table making

  • S:
  • T:
  • A:
  • R:

Adaptation to Tools & Technologies

Learn new software/tools for trial analysis Quick learning, adaptability, proficiency with statistical tools (e.g., SAS, R)

Can you tell me about a time when you had to learn and implement a new statistical software or technology for a clinical trial? How did you manage the learning curve?

Discuss your ability to quickly adapt to new tools, such as SAS, R, or other clinical trial software.

Use of AI

Case: course website with R and quarto

  • S:
  • T:
  • A:
  • R:

Less relevant

Work Under Regulatory Pressure

Manage audits or regulatory scrutiny; maintain accuracy under pressure

Composure, stress management, maintaining statistical precision under high stakes

Describe a situation where you had to manage high levels of regulatory scrutiny or audit during a clinical trial. How did you handle the stress, and how did it affect your statistical work?

Talk about maintaining accuracy and composure under pressure, especially in high-stakes audits.

  • S:
  • T:
  • A:
  • R: