Most technical question was about programming skills
Statistical Interview Questions
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The technical screen included a coding challenge that involved writing a script to generate the first n elements of the Fibonacci sequence, as well as solving a classic two-sum problem: given an array of integers and a target value, return the indices of the two numbers that add up to the target, with the constraint that each input has exactly one solution and elements cannot be reused. In addition to the coding tasks, the interview included statistical questions, specifically on mixed-effects models and Bayes’ theorem, to assess both applied programming skills and foundational statistical knowledge.
Firstly, I had the dissemination test, where I was given some data (10 years across different regions of the UK). I had 30 minutes to: Draw a graph (using pen and paper) Identify five key points from the dataset that I would communicate to the interview panel After this short presentation, the panel asked to see my graph via the camera and explain what they were looking at. They also asked how I would tailor reports and presentations to different audiences, especially with varying levels of understanding — and how I would adapt and explain visualisations I create. Acquiring Data: I was asked how I’ve identified and understood customers’ needs in the past How I implemented quality checks Whether I’ve used open resources and what benefits they have Data Analysis: They asked me to describe two statistical methods I’ve used (e.g. regression analysis, ANOVA, ANCOVA): Why I used them, how, what assumptions were involved, and what outcome they gave These could come from university work (dissertation, MSc, PhD) or professional settings — as long as you clearly understand and explain them. Behavioural Questions: A time when I had to analyse data and deliver under pressure or tight deadlines A time I implemented a change (related to data collection/analysis) and how I supported a colleague through it What I would do if I faced resistance to change from a team member Working Together: Hypothetical scenario: how I would manage conflict in a team, e.g. a colleague not contributing or delaying data/report delivery Overall: I had a very positive impression of the entire process and interview. The panel was professional but human, and the whole structure made sense. I would highly recommend applying for similar roles if this kind of work interests you. Best of luck to everyone reading this!
SAS procedures dealing with complex general linear models.
What skill set has prepared you for this position?
Can you tell us about a time when you had to identify and obtain the most appropriate data to meet customer needs? This could be from academic or professional experience.
Why should we hire you?
- The project-based professor went through each of the experience on my resume and asked questions: 1) introduce a project that you used R/linux, 2) How can you apply your data management experience gained from the industry to this job? - General questions: 1) what's your working style? 2) how do you prioritize multiple tasks? 3) what's your biggest achievement?
What is your previous experience?
No difficult questions were asked.
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