Dell Data Scientist Interview Guide

The gist

Dell is a company for innovative technologists. Born in Michael Dell’s undergrad dorm room at UT, Dell Technologies has been at the forefront of end-to-end solutions, from individual gaming PCs and machine learning to enterprise-level servers, forecasting, and security. The same scrappy spirit of innovation that began in a dorm room has scaled with Dell’s ambitions, and the company now has 30,908 patents and patent applications (including 2000 patents issued in 2023 alone) and $2.8 billion devoted to R&D. If you want to be at the cutting edge of what technology can do as a data scientist, Dell is for you.

The data science interview loops at Dell are team-independent, so there’s variance among each team’s process.  That being said, what remains consistent throughout the teams is that Dell tends to prefer data scientists with experience in at least some of the following:

• Big-picture thinking and communication skills
• Experience in the public and private cloud
• Advanced machine learning algorithms and statistics

What does a Dell Data Scientist do?

Depending on the team, data scientists at Dell will contribute insights, forecasting, and algorithms to a diverse array of projects ranging from enterprise-level security software to internal company A/B testing. At a company as large as Dell, distributed teams work independently, and often collaborate to make sure they’re not reinventing the wheel—so make sure you’re able to describe the big-picture priorities of your projects to other teams, who may be potential collaborators.

Dell is rare in the tech industry for its focus on work-life balance and its employees’ tenure. If you land a job in Dell’s Data Science teams, you may work with people who’ve been there for up to 20 years!

Compensation may vary based on location, but the average total compensation across data science levels at Dell are:

• (Entry-level) Data Scientist: $110K
• Data Scientist: $117K
• Senior Data Scientist: $130K
• Principal Scientist: $170K

Before you apply

• Review machine learning algorithms and statistics, since there’s a lot of overlap between ML/AI and data science at Dell.
• Practice speaking about technical concepts in a way that a nontechnical person can understand. Data scientists at Dell often pitch and explain their work to leadership, so strong data science candidates are “bilingual” in both tech and business.
• Research recent interview questions asked at Dell.
• Check out the Dell Technologies Blog so you can speak about current works in progress at Dell.

Interview process

Note: This guide's questions are based on experiences interviewing candidates for senior-level data science roles. Hiring managers mention that for most senior-level data science and machine learning roles, Dell’s four-step hiring process may take up to three months, with more steps adding potential delays.

Though Dell teams have various processes, generally there are at least four interview stages:

1. Recruiter phone screen to ensure you meet the minimum requirements for the role
2. Hiring manager interviews, where the hiring manager will delve into a recent project
3. Technical screens split into two (sometimes three) separate interviews
4. The final-round interview is focused almost entirely on behavioral questions

Note: Each team’s hiring process is different and highly dependent on the available hiring time. The four-stage process detailed here is typically seen as the “expedited” version. Longer hiring processes may include a final onsite interview where you may have up to five technical and behavioral screens. Some data science candidates also mention being given take-home assessments with tasks similar to the case study-style questions asked in the hiring manager round.

Broadly comparing the philosophy of technical rounds, Dell and Google primarily care about your thought process, whereas Meta and Amazon mainly care about your results. More than Google, though, Dell really wants to know about your work’s big-picture, quantifiable business impact.

1. Recruiter screen

The recruiter phone screen is typically a 30-minute call that may include some light technical questions, but usually the focus is on behavioral questions and recruiter logistics questions.

Be ready to talk about your previous work history and skills as they relate to the job description and why you’re passionate about forecasting, A/B Testing, and machine learning (aka “why data science at Dell”).

Sample questions include:

• Walk me through your resume.
• Why Dell?
• What are you looking for in your next role?
• Tell me about a time you innovated something.
• What was the last decision you made that had a meaningful business impact? What was it, and what was the impact?

2. Hiring manager interview

Hiring managers have a lot of discretion on how they handle their teams’ interviews at Dell. Generally these interviews tend to last around 50 minutes, with a mixed focus on your former projects, team-specific domain questions, and behavioral questions.  Your hiring manager will be using this time to see if you’re someone who can look at a problem differently, so make sure whatever project you showcase also showcases your innovative thinking.

When your hiring manager asks you behavioral questions, they’re looking to see if you can drive projects and values and execute on projects you’re given. They want to see that you’re creative, can take charge, and can talk to managers in a collaborative way. Candidates who can be technically correct are fine, but stellar DS candidates can present and advocate for their ideas to leadership, who may have infrastructure experience without the technical vocabulary.

As well as delving into your personality and past projects, hiring managers may also ask you some straightforward technical questions to assess your know-how. Many Dell Hiring Managers try to ask open-ended technical questions about real-world products, services, and projects the company has produced, but reserve the right to throw in a pop quiz-style question just to keep you on your toes.

Topics include:

• ML algorithms with clustering techniques
• Univariate and multivariate feature selection
• Python
• Transformer Architecture
• Tokenization
• Byte-Pair Encoding
• A/B Testing
• Experimentation

Sample questions include:

• How would you solve this [Scenario] concerning supply chain disruption?
• Create a problem statement. How would you approach it?
• Explain the meaning of the three weight matrices, K, Q, and V in the context of Transformer architecture.
• What are the data science ways that you’ve innovated in previous roles?
• On your former project: How did you look at the problem differently than it was presented to achieve a better outcome?
• On your former project: What are the parameters that you used that really made a difference?
• What are some assumptions of a regression data analysis?

3. Technical screen

This is typically a 60-minute Codepath assessment, supervised by a panel of at least 2–3 people (generally your hiring manager, and at least one more member of their team).  Interviewers have leeway to make up their own questions, and often write them based on recent projects or issues their team has faced, to assess your real-world creativity and problem-solving. As at Google, though, the why and how of your solutions in this interview are a greater priority for Dell than simply providing the what of an under-explained solution.

Hiring managers at Dell often ask data science candidates about machine learning topics as well as more straightforward statistical forecasting questions during this portion, and stellar candidates are able to fluently navigate both domains, since work at Dell often requires you to use both skillsets.

Topics:

• Linear regression
• Lora, QLora, Optimization, RAG
• PyTorch and hugging face model/trainer optimization
• Transformer architecture
• A/B Testing
• Load balancing and public cloud (using Docker or Kubernetes)

Sample questions include:

• Given a set of data, what does the ACF plot say about the data?
• What is LSTM?
• What is the t-statistic of a set of data?
• Tell me about distribution probability.
• Tell me about the architecture of Transformer in detail.
• Tell me about the architecture of BERT in detail.
• What is the difference between a decision tree and a random forest?
• Describe an analytical model from end to end in the context of a past problem you solved.
• What kind of data would you collect to decide if a company should go through with a given initiative?
• Describe a supervised machine learning model and how it works under the hood.
• Take signals from news for our long horizon forecast, and build heuristics to try to predict what a Dell data center will need based on generative AI trends.
• Two-model Ensemble: given a simple model to predict global cash on hand, with one model towards incoming and one towards outgoing, ensemble them, and then look at the sample data and then improve processes.
• Improve a model API, paying attention to details and edge cases, to make sure results are consistent and replicable.
• Given a test data set, write a time series forecast and the EDA leading up to it. How can you package the models better?

4. Final-round interviews

In many rounds of interviewing, your final interview will be with your hiring manager’s skip-level, and your potential team lead. Dell interviews very few candidates for this role—typically 3–5 people per role—so if you make it here, good job!

The questions asked during this 40–50 minute conversation will be similar to the behavioral and project-based questions asked in the hiring manager interview, with the skip level leader looking for innovative, experienced, and communicative candidates who can “win together,” which is a pillar of Dell’s values.

Surprisingly for big tech interview loops, Dell's final round contains few technical questions. This round is focused on advanced behavioral and motivational questions. Make sure to give answers that reflect your quantifiable business impact.

Sample questions include:

• What are the data science ways that you’ve innovated in previous roles?
• Tell me about a time you looked at a problem differently than it was presented to achieve a better outcome. What did you do, and what was the outcome?
• You find out a project your team has invested considerable time into is also a priority of a different team. How do you begin to bring the teams together?
• Why Dell? (Be ready to answer this in more depth than you did during your recruiter screen.)

Additional resources

• Take our course to level up your data science skills.
• Get coaching and actionable feedback from data scientists at the level you aspire to land an offer for.
• Practice with mock interviews on the most common types of problems.

FAQs about Dell DS interviews

What can I expect from my interview at Dell?

You can expect a) a focus on ML and statistics, b) a penchant for communication clear enough for nontehcnical employees, and c) at least four interviews emphasizing not just what you’ve done, but how it’s had quantifiable business impact.

On average, how much do Dell Data Scientists typically make?

The average total compensation across data science levels at Dell are:

• (Entry-level) Data Scientist: $110K
• Data Scientist: $117K
• Senior Data Scientist: $130K
• Principal Scientist: $170K

How long is the typical Dell interview process?

Interviews at Dell will take at least three months, depending on the team you’re interviewing with.

How should I prepare for a data science interview at Dell?

Keep these tips and best practices in mind before your DS interview at Dell:

• Prepare to speak on a recent project in a way that’s accessible to business leadership, not just technical experts, and detail its impact on greater business goals.
• Do some open-source projects, with an eye towards bug fixes and code cleanup, and familiarize yourself with both the public and private cloud.
• Familiarize yourself with Transformer architecture.

Will I have in-person interviews at Dell?

You might have in-person interviews at Dell, depending on the team you interview with, but many Dell teams are globally distributed and have fully remote interviewing.