Research assistants can be employed within many industries or in academic settings to support senior research staff or faculty with their research projects. They help the research team throughout the entire lifecycle of data including idea and methodology generation, conducting literature reviews, running experiments, data collection, analysis, synthesis and report writing. Additionally, Research Assistant can further support senior researchers with administrative tasks like scheduling and conducting interviews or focus groups, providing maintenance for lab equipment, data-entry and managing participant records. Their administrative as well as technical skills in research design and statistical analysis (e.g., R, python, SPSS) supports the research team in generating insights to inform business decisions, solve problems, enhance teams or publish academic research. Performing this role requires technical statistical skills, strong critical/analytical thinking and excellent organizational skills.
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Research Design & Methods
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Data Cleaning
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Applied Statistics
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Data Presentation
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Critical Thinking
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Organizational Skills
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Analytical Thinking
How to effectively interview Research Assistants
While it might seem difficult to figure out whether a candidate will succeed as a Research Assistant in your company, a well-developed set of interview questions that tap into the core skills required to perform in a Research Assistant role will go a long way in helping you decide.
But where do you start? How do you develop a set of great interview questions?
The best interview questions come directly from a job analysis. A job analysis is an evidence-based method that focuses on assessing key features of a particular role. These features describe both the job itself (i.e., tasks, responsibilities, and performance objectives), and the characteristics required of someone to perform successfully in the job (e.g., knowledge, skills, and abilities). A job analysis forms the basis of many HR practices such as compensation, performance management, and - you guessed it - how to interview and hire candidates.
At Hireguide, we’ve done the job analysis work for you. We’ve used the method to identify a core set of skills associated with the Research Assistant role, and we’ve developed and validated a list of behavioral and situational questions with answer guides that tap directly into those core skills. And that’s not all. We’ve compiled these questions and created a Research Assistant Interview Template for you that integrates other interviewing best practices. Skills-based interviews will not only help you make higher quality and evidence-based hiring decisions, but research also shows they enhance fairness and reduce bias in your hiring process.
Example interview questions to ask
Question 1
Describe a time you faced an unexpected problem when analyzing data. How did you handle it, and what were some key takeaways from the experience?
Answer Tips
- Clearly describes the situation and how they identified the problem
- Considered the root cause of the problem to propose an effective solution
- Discusses solutions they considered and justifies their choice
- Considers implications of the problem on the quality of the analysis/results
- Share learnings and best practices to prevent the issue from reoccurring
Question 2
Tell me your process for cleaning and preparing a quantitative dataset for analysis.
Answer Tips
- Explains steps: gathering, cleaning, enriching, validating and storing the data
- Cleans data by checking assumptions (e.g. missing data, outliers, etc.)
- Explains common challenges in the cleaning/preparation process
- Shares examples of challenges they have experienced with the process
- Discusses key learnings and takeaways for improving the process
Question 3
Describe tactics you use to efficiently keep track of research project files, participant information, experiment/interview scheduling and other important details surrounding research processes.
Answer Tips
- Demonstrates logical thinking around filing, organizing and storing information
- Addresses processes to effectively manage scheduling
- Emphasizes importance of anonymity of participant information
- Formulates clear and structured processes and systems
- Discusses implementation and education for the wider research team
