University of Maryland, Baltimore Data Scientist interview questions & guide 2026

The following questions reflect the patterns observed in recent candidate experiences. While specific technical queries may shift based on the current research projects of the hiring team, you should prepare for a rigorous evaluation of your ability to apply statistical methods to medical data.

Technical and Statistical Competency

These questions test your proficiency with the tools and methodologies required for clinical research.

• Describe your experience using SAS for complex data manipulation and statistical modeling.
• How do you handle missing or incomplete data in clinical research sets?

Preparation for a Data Scientist role at University of Maryland, Baltimore requires a balance of deep technical mastery and the ability to articulate your process. You are not just being judged on the correctness of your code, but on the validity of your approach to research.

Role-Related Knowledge – You must demonstrate mastery of SAS and standard statistical packages. Interviewers will look for your ability to select the right tool for clinical data analysis and your understanding of the nuances of medical record data.

Problem-Solving Ability – You will be evaluated on how you structure an ambiguous research question into a testable hypothesis. Focus on explaining your thought process clearly, including how you validate your results and address potential biases in the data.

Communication and Collaboration – Given the high volume of one-on-one interviews with researchers, your ability to build rapport is essential. You must show that you are a reliable, clear communicator who can serve as an extension of the research team.

The interview process at University of Maryland, Baltimore is highly collaborative and geared toward assessing your ability to integrate into established research teams. You should expect a series of one-on-one discussions that move beyond the hiring manager to include the researchers you will support daily. This structure is designed to ensure cultural and functional alignment across the department.

Rigor is a hallmark of this process. Because you are supporting Anesthesiology Faculty, the team values technical accuracy and a deep understanding of research methodologies. Expect a significant technical component—often involving a take-home assessment—to verify your hands-on proficiency with the specific tools used by the department.

This timeline outlines the progression from initial screenings to the deep-dive technical and peer-evaluation stages. Use this to pace your preparation, ensuring you have refreshed your knowledge of both core statistics and the specific software requested by the team.

Technical Proficiency in SAS

Because SAS is a primary tool for this role, you will be expected to demonstrate high-level fluency. This includes data cleaning, merging large datasets, and performing complex statistical analysis.

Be ready to go over:

• Syntax and macro development in SAS.
• Techniques for cleaning and validating clinical datasets.

As a Data Scientist, your primary responsibility is to provide the quantitative backbone for the Anesthesiology Faculty research agenda. You will spend your time cleaning and standardizing clinical data, developing predictive or descriptive models, and preparing results for publication or clinical implementation.

You will act as the bridge between raw data and scientific insight. This involves regular collaboration with clinicians and researchers to define project scopes. You will be expected to manage your own pipeline of tasks, ensuring that all analyses are documented, reproducible, and ready for peer review.

A strong candidate will possess a blend of advanced statistical training and practical experience in a research or healthcare setting.

• Must-have skills: Proficient in SAS, strong understanding of biostatistics, experience with clinical or longitudinal datasets, and excellent technical writing skills.
• Nice-to-have skills: Knowledge of R or Python, experience with electronic health record (EHR) systems, and a background in medical or public health research.

Q: How difficult is the technical assessment? A: The assessment is designed to be practical. It is less about "trick" algorithm questions and more about your ability to perform real-world data manipulation and statistical tasks relevant to the role.

Q: What is the team culture like? A: It is an academic, research-driven environment. You will be working with experts, so expect a culture that values intellectual curiosity, precision, and collaborative feedback.

Q: Will I have to present my work? A: Yes. You may be asked to explain your approach to a previous project or present the results of your technical assessment to the research team.

• Focus on Reproducibility: Emphasize your documentation habits. In research, code that cannot be audited is often useless.
• Prepare for One-on-Ones: Since you will meet many researchers, prepare a concise "elevator pitch" of your experience that highlights how you can support their specific goals.
• Own Your Methodology: If you make a choice about a statistical test, be prepared to explain exactly why that test was the best fit for that specific dataset.

The Data Scientist position at University of Maryland, Baltimore offers a unique opportunity to apply your technical skills to meaningful medical research. By focusing on your SAS proficiency, your grasp of biostatistical principles, and your ability to communicate effectively with research stakeholders, you will be well-positioned to succeed.

Approach your interviews as a series of professional consultations. Demonstrate not just your technical capability, but your commitment to the rigor and precision required in clinical research. With thorough preparation and a clear focus on the research-driven nature of this role, you will be a standout candidate.