Carnegie Mellon University’s Software Engineering Institute (SEI) is a renowned hub for cutting-edge research in various STEM fields, including statistics, mathematics, physics, electrical engineering, and computer engineering. At the SEI, Senior Research Scientists tackle advanced technical challenges for government and industry clients, focusing on quantum communication, quantum computing, quantum sensing, and quantum information science (QiS).

As a Senior Research Scientist at SEI, you will engage in missions critical to national security, working alongside top-tier applied research professionals and university faculty. You will identify technical problems, develop prototype solutions, and contribute to the creation of technologies that influence national security strategies for decades. You'll participate in research projects, author proposals, execute studies, and present findings to DoD sponsors and at academic conferences.

Preparing for this challenging role? Interview Query can help you navigate the interview process at SEI with expert guidance and insightful resources.

Submitting Your Application

The first step in landing a Research Scientist position at the Software Engineering Institute (SEI) of Carnegie Mellon University (CMU) is to submit a compelling application that reflects your technical skills and interest in tackling advanced technical challenges. Carefully review the job description, tailor your CV according to the prerequisites, and craft a targeted cover letter. Highlight your relevant skills, work experiences, and passion for research in your application.

Recruiter/Hiring Manager Call Screening

If your application is shortlisted, a recruiter from the SEI Talent Acquisition Team will contact you for an initial screening call. The recruiter will verify key details about your experiences, skill level, and interest in the role. Behavioral questions may also be a part of this screening process.

In some cases, the hiring manager might join the call to answer your questions about the role and the organization. This conversation typically lasts about 30 minutes and may include surface-level technical and behavioral discussions.

Technical Virtual Interview

Upon successfully navigating the initial screening, you will be invited to a technical interview, which will be conducted virtually via video conference and screen sharing. This 1-hour long interview will focus on your technical expertise, including quantum physics, computer engineering, and other relevant STEM fields.

Expect questions around quantum communication, quantum computing, quantum sensing, and quantum information science (QiS). The interview may also involve problem-solving tasks, algorithm design, and discussions on your previous research work.

Onsite Interview Rounds

Following a second recruiter call with logistical details, you will be invited to attend the onsite interview loop at one of SEI's locations, primarily in Pittsburgh, PA. The onsite interview usually consists of multiple rounds, each assessing different aspects of your technical abilities and fit for the role.

These rounds may cover specialized topics such as statistical analysis, machine learning models, and interdisciplinary collaboration. If you were assigned take-home assignments or given case studies, you might need to present your findings during these interviews.

Quick Tips For SEI Research Scientist Interviews

• Tailor Your Application: Focus on the requirements and preferred qualifications listed in the job description. Highlight any experience you have with quantum technologies, AI, machine learning, or interdisciplinary research.
• Research SEI and CMU: Understand SEI's mission and the type of projects they work on. Be prepared to discuss how your skills and experiences align with their research objectives.
• Technical and Behavioral Preparedness: Brush up on foundational and advanced topics related to quantum communication, machine learning, and interdisciplinary teamwork. Practicing with Interview Query's resources can also help you prepare for both technical and behavioral questions.

Ready to take the next step?

Typically, interviews at Software Engineering Institute | Carnegie Mellon University vary by role and team, but commonly Research Scientist interviews follow a fairly standardized process across these question topics.

• Write a SQL query to select the 2nd highest salary in the engineering department. Write a SQL query to select the 2nd highest salary in the engineering department. If more than one person shares the highest salary, the query should select the next highest salary.

• Write a function to merge two sorted lists into one sorted list. Given two sorted lists, write a function to merge them into one sorted list. Bonus: Determine the time complexity.

• Write a function missing_number to find the missing number in an array. You have an array of integers, nums of length n spanning 0 to n with one missing. Write a function missing_number that returns the missing number in the array. Complexity of (O(n)) required.

• Write a function precision_recall to calculate precision and recall metrics from a 2-D matrix. Given a 2-D matrix P of predicted values and actual values, write a function precision_recall to calculate precision and recall metrics. Return the ordered pair (precision, recall).

• Write a function to search for a target value in a rotated sorted array. Suppose an array sorted in ascending order is rotated at some pivot unknown to you beforehand. Write a function to search for a target value in the array and return its index; otherwise, return -1. Bonus: Your algorithm's runtime complexity should be in the order of (O(\log n)).

• Would you think there was anything fishy about the results of an A/B test with 20 variants? Your manager ran an A/B test with 20 different variants and found one significant result. Would you suspect any issues with these results?

• How would you set up an A/B test to optimize button color and position for higher click-through rates? A team wants to A/B test changes in a sign-up funnel, such as changing a button from red to blue and/or moving it from the top to the bottom of the page. How would you design this test?

• What would you do if friend requests on Facebook are down 10%? A product manager at Facebook reports a 10% decrease in friend requests. What steps would you take to address this issue?

• Why might the number of job applicants be decreasing while job postings remain constant? You observe that the number of job postings per day has remained stable, but the number of applicants has been decreasing. What could be causing this trend?

• What are the drawbacks of the given student test score datasets, and how would you reformat them for better analysis? You have data on student test scores in two different layouts. What are the drawbacks of these formats, and what changes would you make to improve their usefulness for analysis? Additionally, describe common problems in "messy" datasets.

• Is this a fair coin? You flip a coin 10 times, and it comes up tails 8 times and heads twice. Determine if the coin is fair based on this outcome.

• Write a function to calculate sample variance from a list of integers. Create a function that takes a list of integers and returns the sample variance, rounded to 2 decimal places. Example input: test_list = [6, 7, 3, 9, 10, 15]. Example output: get_variance(test_list) -> 13.89.

• Is there anything suspicious about the A/B test results with 20 variants? Your manager ran an A/B test with 20 different variants and found one significant result. Evaluate if there is anything suspicious about these results.

• How to find the median in a list where over 50% of elements are the same? Given a sorted list of integers where more than 50% of the list is the same integer, write a function to return the median value in (O(1)) computational time and space. Example input: li = [1,2,2]. Example output: median(li) -> 2.

• What are the drawbacks of the given student test score data layouts? You have student test score data in two different layouts. Identify the drawbacks of these layouts, suggest formatting changes for better analysis, and describe common problems in "messy" datasets.

• How would you evaluate whether using a decision tree algorithm is the correct model for predicting loan repayment? You are tasked with building a decision tree model to predict if a borrower will pay back a personal loan. How would you evaluate if a decision tree is the right choice, and how would you assess its performance before and after deployment?

• How does random forest generate the forest, and why use it over logistic regression? Explain the process by which a random forest generates its ensemble of trees. Additionally, discuss the advantages of using random forest compared to logistic regression.

• When would you use a bagging algorithm versus a boosting algorithm? Compare two machine learning algorithms. Describe scenarios where you would prefer a bagging algorithm over a boosting algorithm, and discuss the tradeoffs between the two.

• How would you justify using a neural network for a business problem and explain its predictions to non-technical stakeholders? Your manager asks you to build a neural network model to solve a business problem. How would you justify the complexity of this model and explain its predictions to non-technical stakeholders?

• What metrics would you use to track the accuracy and validity of a spam classifier? You are tasked with building a spam classifier for emails and have completed a V1 of the model. What metrics would you use to evaluate the model's accuracy and validity?

What is the average salary for a Research Scientist at Software Engineering Institute | Carnegie Mellon University?

Q: What is the role of a Research Scientist at the Software Engineering Institute (SEI) at Carnegie Mellon University? Research Scientists at the SEI leverage advanced interdisciplinary skills in STEM fields to help government and industry clients tackle advanced technical challenges. This involves identifying problem areas, developing prototype solutions, and presenting findings to clients and at academic conferences.

Q: What qualifications are required for the Research Scientist position? A BS in computer science, statistics, engineering, physics, mathematics, or a related discipline with three years of experience, an MS with one year of experience, or a PhD in similar fields. Additionally, candidates must be legally authorized to work for CMU in the United States and must be able to obtain and maintain a U.S. Department of Defense security clearance.

Q: What kind of projects will I be involved in as a Research Scientist at SEI? You will participate in groundbreaking research in areas such as quantum communication, quantum computing, quantum sensing, and QiS. You will collaborate with elite applied research professionals and university faculty to influence national security strategy through innovative technologies.

Q: What are the key skills and abilities needed for success in this role? Candidates should have a background in quantum technologies, strong teamwork skills, the ability to work independently on complex tasks, and the ability to convey technical information clearly to diverse audiences. Innovative thinking and thriving in a multi-disciplinary environment are also essential.

How can I prepare for an interview for this position? To prepare, research the SEI's work and its impact on national security. Practice common interview questions on technical and behavioral aspects and review your technical skills. Interview Query is an excellent resource to help you practice and refine your interview skills.

Are you passionate about shaping the future of technology and national security? The Software Engineering Institute (SEI) at Carnegie Mellon University offers a dynamic environment where you can collaborate with elite researchers and faculty to tackle groundbreaking challenges in quantum communication, computing, and machine learning. As a Research Scientist, you will contribute to projects that have a lasting impact on national security strategies, working within interdisciplinary teams to develop innovative solutions and publish your findings in prestigious platforms.

If you want more insights about the company, check out our main Software Engineering Institute Interview Guide, where we have covered many interview questions that could be asked. At Interview Query, we empower you to unlock your interview prowess with a comprehensive toolkit, equipping you with the knowledge, confidence, and strategic guidance to conquer every interview question and challenge.

You can check out all our company interview guides for better preparation, and if you have any questions, don’t hesitate to reach out to us.

Good luck with your interview!