Draper is a renowned engineering innovation company that advances technology through excellence in systems engineering and deep domain technology capabilities. It has an impressive history of contributing to national security, space systems, and precision healthcare.

As a Data Scientist at Draper, you will be part of a team working on cutting-edge projects that require top-notch analytical skills and a comprehensive knowledge of data science techniques. You'll be expected to engage in tasks such as data mining, statistical analysis, predictive modeling, and providing insights to inform decision-making processes.

In this guide, we will walk you through the interview process for the Data Scientist position at Draper, covering common interview questions and offering valuable tips to secure your role. Whether you are looking to break into the field or advance your career, this guide will help you prepare effectively.

Submitting Your Application

The application process at Draper for the Data Scientist role begins with submitting a detailed and well-tailored application. Take the time to review the job description and align your CV and cover letter to highlight your technical skills, relevant work experiences, and genuine interest in joining Draper. Incorporating specific keywords and showcasing your analytical capabilities can increase the chances of your application standing out.

Recruiter/Hiring Manager Call Screening

If your application makes it to the shortlist, a recruiter from Draper's Talent Acquisition Team will reach out to confirm your skills and experience. This initial screening may include behavioral questions to understand your fit for the role. In some instances, the hiring manager for the Data Scientist position may participate in this call to provide more insights into Draper and the job responsibilities. The duration of this screening call is typically around 30 minutes.

Technical Virtual Interview

Upon successfully passing the recruiter screening, you will be invited to a technical virtual interview. This stage involves a mix of video conferencing and screen sharing with Draper's technical team. The focus will be on your proficiency with data systems, ETL pipelines, SQL queries, and other relevant technical skills. You might also be given take-home assignments involving data visualization, product metrics, hypothesis testing, and basic machine learning concepts. This interview generally lasts for about an hour.

Onsite Interview Rounds

Following a further discussion with the recruiter about the next steps, you will be invited to Draper's office for onsite interview rounds. These rounds will comprehensively cover various aspects of the Data Scientist role, including programming, machine learning models, and your ability to derive actionable insights from data. Depending on the assignments you completed earlier, you may need to present your solutions during a presentation round. The onsite interviews will help Draper assess your technical skills and cultural fit for the company.

Quick Tips For Draper Data Scientist Interviews

• Understand Draper's Work and Values: Draper’s projects span various industries including defense, space, and health. Familiarize yourself with their work and think about how your past experiences can align with their mission.

• Master Your Technical Skills: Ensure you're well-versed in the technical aspects required for the role, such as SQL, Python, R, ETL processes, and basic machine learning models. Practice these skills thoroughly using resources like Interview Query.

• Behavioral Preparation: Reflect on your previous professional experiences to articulate clear and concise answers to behavioral questions. Emphasize teamwork, problem-solving, and how you handle challenges, keeping in mind Draper’s collaborative environment.

Typically, interviews at Draper vary by role and team, but commonly Data Scientist interviews follow a fairly standardized process across these question topics.

• Identify all duplicate values in a list of integers. Given a list of integers, identify all the duplicate values in the list. Assume that the list can contain both positive and negative numbers, and the order of the list does not matter. A number is considered a duplicate if it appears more than once in the list. Return a list of the duplicate numbers.

• Select the five most expensive projects by budget to employee count ratio. We want to select the five most expensive projects by budget to employee count ratio. Account for duplicate rows in the employee_projects table and write a query to select the top five projects.

• Create a subquery or common table expression to find the top 3 ads by popularity. Create a subquery or common table expression named top_ads containing the top 3 ads by popularity. Return the number of rows resulting from different join operations between ads and top_ads.

• Find employees who joined before their manager. You're given two tables: employees and managers. Find the names of all employees who joined before their manager.

• Write a function to rotate a matrix by 90 degrees clockwise. Given an array filled with random values, write a function rotate_matrix to rotate the array by 90 degrees in the clockwise direction.

• How do we select the best 10,000 customers for a pre-launch of a new show? You are working as a data scientist at Amazon Prime Video, and they want to test the launch of a new show on 10,000 customers first. How would you select the best 10,000 customers for this pre-launch?

• What is the process for pre-launching a TV show on Amazon Prime to measure performance? Describe the steps involved in pre-launching a TV show on Amazon Prime to measure its performance.

• How would you evaluate the results of an A/B test on free shipping to determine success? You work at an eCommerce startup and ran an A/B test on the checkout product page to see if surfacing free shipping increases conversions. The control group had no specification of free shipping, while the experiment group did. How would you evaluate the results and determine if the test was successful?

• How would you conduct an experiment to test displaying ETA as a range and determine significance? You work at Uber, and a PM suggests displaying ETA as a range (e.g., 3-7 minutes) instead of a direct estimate. How would you conduct this experiment and determine if the results are significant?

• How would you decide whether Google should build a game feature for Google Home? You are tasked with pitching a new feature for Google Home, and a co-worker suggests building a game feature. How would you decide whether Google should build it?

• How would you measure the effectiveness of extra pay for delivery drivers during peak hours? You work at a food delivery company. How would you measure the effectiveness of giving extra pay to delivery drivers during peak hours to meet consumer demand?

• What is the difference between Logistic and Linear Regression? When would you use one instead of the other? Explain the key differences between Logistic and Linear Regression. Describe scenarios where each method is more appropriate to use in practice.

• How would you explain what a p-value is to someone who is not technical? Explain the concept of a p-value in simple terms to someone without a technical background. Use analogies or everyday examples to make it understandable.

• What is the difference between Logistic and Linear Regression? When would you use one instead of the other in practice? Describe the key differences between Logistic and Linear Regression. Provide examples of scenarios where each method would be appropriately applied in practice.

What is the average salary for a Data Scientist at Draper?

Q: What is the interview process for a Data Scientist position at Draper like?
The interview process at Draper typically begins with an initial phone screening with HR, followed by a technical interview. If you pass these stages, you’ll be invited to an onsite interview, which includes technical assessments, case studies, and behavioral questions to evaluate both your skills and cultural fit.

Q: What qualifications are Draper looking for in a Data Scientist candidate?
Draper looks for candidates with a strong background in statistics, programming, and machine learning. Proficiency in tools like Python, R, and SQL, as well as experience with data visualization techniques, are highly valued. Furthermore, a candidate should have excellent problem-solving skills and the ability to communicate complex data insights effectively.

Q: Can you give some examples of the kind of work a Data Scientist at Draper might do?
Data Scientists at Draper work on various projects, including developing predictive models, conducting trend analysis, and optimizing systems using machine learning algorithms. They also collaborate with cross-functional teams to turn data insights into actionable business strategies.

Q: What is the company culture like at Draper for Data Scientists?
Draper prides itself on a collaborative and innovative culture, encouraging data scientists to experiment and learn continuously. The company values diversity, creativity, and a forward-thinking mindset, ensuring a dynamic and supportive working environment.

Q: How can I prepare for a Data Scientist interview at Draper?
To prepare for your interview at Draper, it’s essential to brush up on your technical skills and review basic statistics, machine learning concepts, and programming tasks. Utilize resources like Interview Query to practice common data science interview questions and scenarios. Don’t forget to study Draper’s recent projects and achievements to understand their data-driven approach.

If you want more insights about the company, check out our main Draper Interview Guide, where we have covered many interview questions that could be asked. We’ve also created interview guides for other roles, such as software engineer and data analyst, where you can learn more about Draper’s interview process for different positions.

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 Draper data scientist 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!