The Research Scientist Interview Questions & More! (Updated for 2024)

The divide between research scientists and data scientists isn’t clearly defined. Still, research scientists are responsible for building and developing models in a niche field using complex machine learning, mathematics, and deep learning theory.

While data scientists and adjacent positions work with broad swaths of data and metrics, research scientists encapsulate a deep understanding within a specific area of expertise, working cross-functionally with different teams to develop prototypes and validate hypotheses.

This article dives into what research scientists do, the skills needed, top hiring companies, and key research scientist interview questions to help you succeed.

The requirements for research scientists largely vary by company: some have more stringent standards, while others are more flexible on the number of years of experience, degree levels, etc. Even within companies, job qualifications can change between teams, so double-check for positions you’re interested in.

Generally, you can be sure to expect the following:

• Strong programming experience: Python or C++ is definitely the go-to for many top companies, but some also accept qualifications similar to other programming languages. ‌‌
• M.S., Ph.D. in a relevant field: Looking at top employers, a Master’s is often the minimum requirement for research scientists. Relevant fields generally include robotics, statistics, computer science, etc. Note: industry experience can compensate for different degrees, i.e., “B.S. with 3 years of industry experience”. ‌‌
• Experience with Deep Learning and Machine Learning: This largely varies by company and field, but many positions require you to understand how to apply machine learning concepts to different solutions. ‌‌
• All Things Data: You should be very familiar with data analysis and visualization and how to redirect your analyses into actionable insights.

For some companies and positions, there’s also an additional, rather unique, requirement:

• Heavy research experience: First-author publications and experience publishing at top-tier conferences are important and a large indicator of your involvement and experience within different projects.

To illustrate the sheer variety in research scientist roles across different companies, here are some examples of open positions in top-tier companies within tech and other industries. Please do note: several of the given examples of research scientist positions at these companies are hiring at the mid to senior level, so the requirements listed may not reflect the qualifications needed for research scientists as a whole.

1. Lyft‌‌ Research Scientist Interview

Lyft has several open positions worldwide for the general Research Scientist position. Within this role, you’d work with engineers and product analysts on different teams to analyze data and provide business insights. ‌

‌This company has rather stringent requirements, looking at candidates with an M.S., at least four years of industry experience, and several additional preferences. ‌‌

In addition, positions with specific designations and divisions (such as “Research Scientist, Autonomous Driving”) work with small, highly specialized teams to develop certain products and services, often within industry-breaking roles. These jobs have higher requirements: a Ph.D., deep learning knowledge, publishing experience, etc.

2. Meta Research Scientist Interview

Compared to Lyft, which has a variety of general Research Scientist positions and specialized ones, Meta organizes all of its research scientists into specific divisions. Here are some examples currently open worldwide:‌‌

• Research Scientist (Perpetual Research)‌‌
• Research Scientist (AI)‌‌
• Research Scientist (Privacy Research)‌‌
• Research Scientist (Neural Interface Interactions)

Depending on the area, these positions often require a Ph.D. in a relevant field, at least a year’s worth of lab experience, and first-author publications, along with extensive experience involving different concepts, skills, and techniques, depending on the position.

3. LinkedIn Research Scientist Interview

The LinkedIn research scientist role is comparable to a combination of Lyft’s general research scientist responsibilities and Meta’s hiring requirements. ‌‌

The research scientist job at LinkedIn involves data manipulation and organization, with variable allowances for specific teams. Candidates are generally expected to have an M.S. or PhD in relevant fields, with several years of industry experience, depending on the specific role. ‌‌

Other qualifications primarily depend on the team you’re applying for. For instance, the AI team requires in-depth machine learning knowledge to develop algorithms within the job search function. ‌

4. Google Research Scientist Interview

Google offers various Research Scientist positions across its global offices, focusing on cutting-edge technologies in AI, machine learning, and other innovative fields. These roles often involve collaboration with interdisciplinary teams to conduct groundbreaking research and develop solutions directly impacting Google’s products and services.

Google’s requirements are highly competitive, typically expecting candidates to hold a Ph.D. in a relevant field, a strong publication record in top-tier conferences, and extensive experience with machine learning frameworks, programming languages, and data analysis tools. Specialized roles, such as “Research Scientist, Quantum Computing,” demand deep expertise in niche areas, emphasizing Google’s focus on leading-edge advancements.

5. Amazon Research Scientist Interview

Amazon’s Research Scientist positions span diverse areas, including natural language processing, robotics, and applied machine learning, to enhance customer experience and operational efficiency. You’ll work alongside engineers and product managers in these roles to drive innovations across Amazon’s ecosystem, such as Alexa, AWS, and fulfillment technologies.

Candidates are expected to have a Ph.D. or Master’s degree in fields like computer science or statistics, with several years of industry or academic experience. Strong analytical skills, proficiency in programming, and expertise in areas like deep learning or optimization are essential. Specific teams, such as Alexa AI or Amazon Robotics, may also require hands-on experience in building scalable systems or conducting large-scale experiments.

As always, several key steps exist in the interview process for a research scientist position. Here’s a broad framework of what you can expect, though it definitely varies by company.

Initial Phone Screen‌‌

This interview will be conducted either with a recruiter or a hiring manager. General topics to be covered will include your past experience, your resume, and certain projects you’ve worked on that relate to the position. This is a general ‘getting to know you’ conversation between you and the company, so just relax and put your best foot forward. ‌‌

Technical Interview‌‌

This is (most likely) another phone interview where you’ll be expected to demonstrate technical knowledge specifically pertaining to the research scientist position. Common subjects will most likely be tied around machine learning concepts, analyzing case studies, and basic statistical concepts. The difficulty and breadth of the questions in this interview depend on the position’s focus. ‌‌ Note: Some interviewers may combine the initial phone screen and the technical interview or skip the former altogether, so ensure you’re always prepared! ‌‌

On-Site Interview‌‌

The on-site interview is the last part of the interview process for research scientists. At this point, you have passed the basic screening and adequately demonstrated your technical knowledge, so this interview is more of an assessment of your fit within the company and, if relevant, within the specific team. ‌‌

You can expect lots of behavioral-type questions and potentially more technical questions relating to the team’s current projects. Here, the technical interview will focus less on the range of your knowledge and more on your approach and justifications for specific parts of the problem. ‌‌

Culture and fit questions are sure to come up, so it’s a good idea to research company values and learn more about the team’s goals before going into the interview. ‌‌

Finally, the structure of the on-site interview largely depends on the company itself. Larger, more established companies, like Meta, Amazon, Google, etc., likely have multiple interviewers and rounds for the on-site part, meaning you may be interviewing most of the day with different members of the team, other research scientists, and so on. ‌

What are the types of interview questions for research scientists?

How does the X concept work? / What are the assumptions of X? / How would you apply X?‌‌

You get the point: This type of question basically asks for a textbook recall of different machine learning concepts and their applications or conditions. ‌‌

Don’t overcomplicate it! Interviewers here are just checking that you know and understand basic concepts. For research scientists specifically, you can definitely count on basic machine learning concepts to come up at least once. Other common topics can range from different statistical applications to programming questions.

1. Case Study‌‌ ‌‌

Case study interview questions may be asked during the technical screening of research scientists’ roles but almost definitely within the on-site interview. ‌‌

Here, the focus isn’t so much on the specific methodology or content (although you don’t want to be spewing out total nonsense) but more on your approach– your choices toward different features and their trade-offs. You should be good to go if you can justify your approach and actively talk through the problem with the interviewer. ‌‌

2. Product/Feature Questions‌‌

This type of question requires more individual research into the specific team and company you’re applying for. The structure of this question will follow along with “How would X change as Y changes?” where X and Y may constitute different variables in team projects. ‌‌

Basically, this question really comes down to the commitment to your preparation. The interviewer is looking to evaluate whether you know the company’s goals, your team’s focus, and your position’s overall objective. ‌‌‌‌‌‌

3. Coding Questions

Coding questions come up pretty frequently for research scientist positions. Almost all research scientists at tech companies have to develop and simulate their ideas and theories in practice before handing them off to an engineer actually to scale.

Most research scientists’ coding interview questions involve testing mathematical and algorithmic concepts. You could be asked to simulate different random variables (binomial, Bayes) or simulations (Monte Carlo).