Research Foundation Of The City University Of New York Data Analyst Interview Questions + Guide in 2025

The Research Foundation of The City University of New York (RFCUNY) is dedicated to enhancing public education by supporting research initiatives and providing essential resources to faculty and staff at CUNY's extensive network of colleges.

As a Data Analyst, your role will be pivotal in driving the evaluation and improvement of educational programs within CUNY's Office of Applied Research, Evaluation, and Data Analytics (OAREDA). You will be responsible for managing evaluation projects that align with the university's mission of promoting college readiness, access, success, and workforce development. Key responsibilities include conducting quantitative and qualitative analyses, developing data visualizations, and effectively communicating your findings to diverse stakeholders. A strong proficiency in statistical software, particularly R, will be crucial for analyzing and manipulating large datasets. As an ideal candidate, you should possess a keen attention to detail, excellent organizational skills, and the ability to work collaboratively under tight deadlines. Your experience in applied research settings, coupled with a solid understanding of statistical concepts and evaluation methods, will make you an asset to the team.

This guide will help you prepare for a job interview by equipping you with a clear understanding of the expectations and skills required for the Data Analyst role at RFCUNY, enabling you to effectively showcase your qualifications during the interview process.

The interview process for a Data Analyst position at the Research Foundation of the City University of New York is structured to assess both technical skills and cultural fit within the organization. The process typically unfolds in several key stages:

1. Initial Phone Interview

The first step is a brief phone interview, usually lasting around 10-15 minutes. During this call, a recruiter will ask a few targeted questions to gauge your interest in the role and your relevant experience. This is also an opportunity for you to learn more about the organization and the specific expectations for the Data Analyst position.

2. Panel Interview

If you successfully pass the initial screening, you will be invited to a panel interview. This stage generally lasts about 45 minutes and involves multiple interviewers, including potential team members and supervisors. The focus here is on your research skills and experience, particularly in data analysis and evaluation methods. Expect questions that explore your past projects, methodologies used, and how you approach problem-solving in a research context.

3. Writing Exercise

Following the panel interview, candidates may be asked to complete a writing exercise. This task is designed to evaluate your ability to communicate complex data findings clearly and effectively. You will likely be given a dataset and asked to produce a report or presentation that summarizes your analysis and insights. This exercise is crucial as it demonstrates your analytical skills and your ability to convey information to various stakeholders.

4. Final Interview

In some cases, a final interview may be conducted with a senior member of the Evaluation Unit or a potential supervisor. This interview may delve deeper into your technical skills, particularly your proficiency with statistical software and data visualization tools. It may also cover your experience with project management and collaboration with program partners.

As you prepare for these stages, consider the specific skills and experiences that align with the role, as they will be central to the interview discussions. Next, let’s explore the types of questions you might encounter during the interview process.

Here are some tips to help you excel in your interview.

Understand the Evaluation Process

Given the focus of the role on evaluation and data analysis, familiarize yourself with the evaluation methodologies commonly used in educational settings. Be prepared to discuss your experiences with both quantitative and qualitative research methods, as well as how you have applied these in previous roles. Highlight any specific projects where you successfully managed evaluation processes, as this will demonstrate your capability to handle the responsibilities of the position.

Prepare for Panel Interviews

The interview process may include a panel format, as indicated by previous candidates' experiences. Practice articulating your thoughts clearly and concisely, as you may be asked a series of questions from different interviewers. Consider preparing a few key examples that showcase your skills in data analysis, project management, and communication. This will help you respond effectively to each panel member's question while maintaining a cohesive narrative about your qualifications.

Showcase Your Technical Skills

Proficiency in statistical software, particularly R, is crucial for this role. Be ready to discuss your experience with data manipulation and analysis, including any specific techniques you have employed, such as regression analysis or data visualization. If you have experience with other tools like Tableau or Excel, be sure to mention these as well. Demonstrating your technical expertise will reassure the interviewers of your ability to handle the data-centric aspects of the job.

Communicate Clearly and Effectively

Strong communication skills are essential for this role, especially when it comes to presenting evaluation findings. Practice summarizing complex data insights in a way that is accessible to diverse audiences. You may be asked to explain how you would communicate results to stakeholders who may not have a technical background. Consider preparing a brief presentation or report that you can reference during the interview to illustrate your ability to convey information clearly.

Emphasize Collaboration and Flexibility

The role requires working closely with program partners and stakeholders. Be prepared to discuss your experiences in collaborative environments and how you have navigated challenges in team settings. Highlight your ability to adapt to changing circumstances and your commitment to maintaining open lines of communication with colleagues and partners. This will demonstrate your alignment with the collaborative culture at the Research Foundation of CUNY.

Reflect on Your Research Experience

Since the role involves significant research responsibilities, be ready to discuss your past research projects in detail. Focus on your role in these projects, the methodologies you employed, and the outcomes achieved. This will not only showcase your research skills but also your ability to contribute to the foundation's mission of driving program improvement through data.

By following these tips and preparing thoroughly, you will position yourself as a strong candidate for the Data Analyst role at the Research Foundation of CUNY. Good luck!

In this section, we’ll review the various interview questions that might be asked during an interview for a Data Analyst position at the Research Foundation of the City University of New York. The interview process will likely focus on your analytical skills, experience with data management, and ability to communicate findings effectively. Be prepared to discuss your research experiences, statistical knowledge, and how you approach data-driven decision-making.

Experience and Background

1. What are your experiences with each stage of the research process?

This question aims to assess your familiarity with the research process and your ability to navigate through its various stages.

How to Answer

Discuss your experience in designing research studies, collecting data, analyzing results, and reporting findings. Highlight specific projects where you played a significant role in these stages.

Example

“I have been involved in multiple research projects where I was responsible for designing the study, collecting data through surveys, and analyzing the results using statistical software. For instance, in my last project, I led a team that evaluated a college readiness program, where I managed data collection and performed quantitative analysis to assess its effectiveness.”

Data Analysis and Tools

2. Can you describe your experience with statistical software, particularly R?

This question evaluates your technical skills and familiarity with tools essential for data analysis.

How to Answer

Provide details about your proficiency with R, including specific functions or packages you have used. Mention any projects where you applied these skills.

Example

“I have extensive experience using R for data analysis, particularly in manipulating large datasets and performing statistical tests. In my previous role, I utilized R to conduct regression analyses and create visualizations that helped stakeholders understand the impact of our educational programs.”

3. How do you ensure data quality and integrity in your analyses?

This question assesses your attention to detail and understanding of data management practices.

How to Answer

Discuss the methods you use to validate data, such as cross-referencing sources, cleaning datasets, and implementing checks for accuracy.

Example

“To ensure data quality, I always start by cleaning the datasets, checking for missing values, and verifying data against original sources. I also implement validation checks throughout the analysis process to catch any discrepancies early on.”

4. Describe a time when you had to present complex data findings to a non-technical audience. How did you approach it?

This question gauges your communication skills and ability to translate technical information into understandable insights.

How to Answer

Explain your approach to simplifying complex data and the tools you used to present your findings effectively.

Example

“In a previous project, I had to present the results of a program evaluation to a group of stakeholders with varying levels of technical expertise. I created a series of visualizations using Tableau that highlighted key findings and trends, and I focused on storytelling to make the data relatable and actionable.”

5. What methods do you use for data visualization, and why are they important?

This question explores your understanding of data visualization techniques and their significance in data analysis.

How to Answer

Discuss the tools you use for visualization and the principles you follow to create effective visual representations of data.

Example

“I primarily use Tableau for data visualization because it allows for interactive dashboards that can engage users. I focus on clarity and simplicity in my visualizations, ensuring that they highlight the most important insights without overwhelming the audience with too much information.”

Research and Evaluation Methods

6. Can you explain the difference between qualitative and quantitative research methods?

This question tests your understanding of research methodologies and their applications.

How to Answer

Define both methods and provide examples of when you would use each in a research context.

Example

“Qualitative research focuses on understanding concepts and experiences through interviews or focus groups, while quantitative research involves numerical data and statistical analysis. For instance, I would use qualitative methods to explore student experiences in a program, and quantitative methods to measure the program's impact on academic performance.”

7. Describe your experience with quasi-experimental methods in program evaluation.

This question assesses your knowledge of evaluation techniques and their application in real-world scenarios.

How to Answer

Discuss specific quasi-experimental methods you have used, such as propensity score matching, and the context in which you applied them.

Example

“I have utilized propensity score matching in a program evaluation to compare outcomes between participants and non-participants. This method allowed me to control for confounding variables and provide a more accurate assessment of the program's effectiveness.”

8. How do you approach developing an evaluation plan for a new project?

This question evaluates your strategic thinking and planning skills in the context of program evaluation.

How to Answer

Outline the steps you take to create an evaluation plan, including stakeholder engagement, defining objectives, and selecting appropriate methods.

Example

“When developing an evaluation plan, I start by engaging with stakeholders to understand their goals and expectations. I then define clear objectives for the evaluation, select appropriate qualitative and quantitative methods, and establish a timeline for data collection and analysis.”

9. What strategies do you use to manage multiple projects simultaneously?

This question assesses your organizational skills and ability to prioritize tasks effectively.

How to Answer

Discuss your project management techniques, such as using tools for tracking progress and setting deadlines.

Example

“I use project management software to keep track of deadlines and deliverables for multiple projects. I prioritize tasks based on urgency and importance, and I regularly communicate with team members to ensure everyone is aligned and aware of project statuses.”

10. How do you stay updated with the latest trends and developments in data analysis and evaluation?

This question gauges your commitment to professional development and staying informed in your field.

How to Answer

Mention specific resources you use, such as journals, online courses, or professional organizations, to keep your skills current.

Example

“I regularly read industry journals and participate in webinars to stay informed about the latest trends in data analysis and evaluation. I also engage with professional organizations, which provide valuable networking opportunities and access to new research and methodologies.”