System1 Research Scientist Interview Questions + Guide in 2025

System1 is a data-driven marketing technology company that focuses on optimizing consumer engagement using behavioral data insights.

The Research Scientist role at System1 is pivotal in harnessing complex datasets to derive actionable insights that inform strategic decisions. Key responsibilities include designing and conducting experiments, analyzing data to identify trends and patterns, and collaborating with cross-functional teams to implement findings. Candidates should possess strong analytical skills, proficiency in programming languages such as Python and SQL, and a solid understanding of statistical methodologies, including Bayesian statistics. A successful Research Scientist will exhibit a proactive approach to problem-solving and the ability to communicate technical concepts effectively to non-technical stakeholders, reflecting System1's commitment to transparency and collaboration.

This guide will help you prepare for interviews by outlining what to expect in terms of questions and the skills that are highly valued at System1, giving you the confidence to present yourself as a strong candidate.

The interview process for a Research Scientist at System1 is structured to assess both technical expertise and cultural fit within the team. It typically unfolds over several stages, allowing candidates to showcase their skills and experiences while also getting a sense of the company environment.

1. Initial Screening

The process begins with an initial screening, usually conducted by an HR representative. This 30-minute phone interview focuses on your background, experience, and how you align with System1's values and culture. Expect to discuss your resume in detail and provide insights into your career aspirations.

2. Technical Assessment

Following the initial screening, candidates often participate in a technical assessment. This may involve a video interview with a technical manager or team lead, where you will be asked to solve problems related to your field of expertise. You might be given a task in advance, such as creating an Excel pivot chart or writing a Python script, to demonstrate your analytical skills and technical knowledge.

3. In-Depth Interviews

Candidates typically undergo multiple in-depth interviews, which can range from three to four rounds. These interviews often include a mix of behavioral and technical questions. You will meet with various team members, including business leads and technical experts, who will evaluate your problem-solving abilities and how you approach challenges. Expect discussions around your previous projects, statistical methods, and analytical case studies relevant to System1's business model.

4. Onsite Interview

The final stage usually involves an onsite interview, where candidates spend several hours interacting with team members and leadership. This may include a presentation of your prior work, discussions about your approach to research, and technical questions that assess your understanding of statistics and programming. The atmosphere is generally collaborative, allowing you to gauge the team dynamics and company culture.

5. Final Evaluation

After the onsite interviews, candidates may be asked to complete a take-home test or coding challenge to further evaluate their skills. The entire process is typically fast-paced, with quick turnaround times between each stage, ensuring that candidates receive timely feedback.

As you prepare for your interview, consider the types of questions that may arise during this process.

Here are some tips to help you excel in your interview.

Understand the Company Culture

System1 has a fast-paced and dynamic environment, which can sometimes feel rushed. It's essential to familiarize yourself with the company's values and recent developments, especially following their IPO. Pay attention to employee reviews to gauge the work atmosphere and team dynamics. This knowledge will help you tailor your responses and demonstrate that you are a good cultural fit.

Prepare for a Multi-Round Process

Expect a structured interview process that may involve multiple rounds, including phone interviews with HR, technical assessments, and discussions with various team members. Be ready to articulate your experience clearly and concisely, as interviewers will likely ask you to walk them through your resume and past projects. Practice summarizing your work in a way that highlights your contributions and the impact of your research.

Showcase Technical Proficiency

As a Research Scientist, you will be expected to demonstrate strong technical skills, particularly in programming languages like Python and statistical analysis. Be prepared for technical questions that may involve coding challenges or problem-solving scenarios. Brush up on relevant concepts, such as Bayesian statistics and SQL, and be ready to discuss how you would approach specific analytical tasks.

Emphasize Communication Skills

System1 values team collaboration and interpersonal skills. During your interviews, focus on how you communicate complex ideas and work effectively within a team. Be prepared to discuss your work style and how you handle feedback and collaboration. Interviewers will be assessing not only your technical abilities but also whether you would be a pleasant addition to the team.

Be Ready for Behavioral Questions

Expect a mix of behavioral and situational questions that assess your problem-solving abilities and how you handle challenges. Prepare examples from your past experiences that demonstrate your critical thinking, adaptability, and resilience. Use the STAR (Situation, Task, Action, Result) method to structure your responses, ensuring you convey the context and outcomes of your actions.

Stay Calm and Engaged

Interviews at System1 can be intense, but maintaining a calm demeanor is crucial. Engage with your interviewers by asking insightful questions about the team and projects. This not only shows your interest in the role but also helps you gauge if the environment aligns with your expectations. Remember, interviews are a two-way street, and your comfort with the team is just as important as their assessment of you.

Follow Up Thoughtfully

After your interviews, consider sending a personalized thank-you note to your interviewers. Mention specific topics discussed during your conversations to reinforce your interest in the role and the company. This small gesture can leave a positive impression and demonstrate your professionalism.

By following these tips, you can approach your interview with confidence and clarity, positioning yourself as a strong candidate for the Research Scientist role at System1. Good luck!

Experience and Background

1. Can you describe your process for taking over a project?

Understanding how you approach project transitions is crucial, as it reflects your organizational skills and ability to adapt to new challenges.

How to Answer

Discuss your methodology for assessing the current state of the project, identifying key stakeholders, and formulating a plan for moving forward. Highlight your communication skills and how you ensure a smooth transition.

Example

“When taking over a project, I first conduct a thorough review of existing documentation and meet with the previous project lead to understand the current status. I then identify key stakeholders and set up a meeting to discuss their expectations and any immediate concerns. This approach allows me to create a clear action plan that aligns with the team’s goals.”

2. Talk us through your resume.

This question allows you to highlight your relevant experiences and how they align with the role.

How to Answer

Provide a concise overview of your professional journey, emphasizing experiences that are particularly relevant to the position. Focus on achievements and skills that demonstrate your fit for the role.

Example

“I started my career in data analysis, where I developed a strong foundation in statistical methods. I then transitioned to a research role, focusing on machine learning applications in marketing analytics. My recent project involved developing a predictive model that improved customer targeting, which resulted in a 20% increase in conversion rates.”

3. How familiar are you with Python?

Python is a key programming language for data analysis and machine learning, so demonstrating your proficiency is essential.

How to Answer

Discuss your experience with Python, including specific libraries or frameworks you have used. Mention any projects where you applied Python to solve real-world problems.

Example

“I have extensive experience with Python, particularly in data manipulation using Pandas and NumPy. In my last project, I used Python to build a machine learning model that analyzed customer behavior, which helped the marketing team optimize their campaigns.”

4. Suppose you noticed a KPI for one of our ML models dipped sharply and then recovered over a span of an hour yesterday. What would you do to investigate?

This question assesses your analytical thinking and problem-solving skills in a real-world scenario.

How to Answer

Outline a systematic approach to diagnosing the issue, including data analysis, stakeholder communication, and hypothesis testing.

Example

“I would start by reviewing the logs and metrics from the time the KPI dipped to identify any anomalies. I would also check for any changes in the data inputs or model parameters. If necessary, I would consult with the data engineering team to ensure there were no issues with data integrity during that period.”

5. Discuss why you did your project the way you did.

This question allows you to explain your decision-making process and the rationale behind your project choices.

How to Answer

Articulate the objectives of the project, the challenges you faced, and how your decisions contributed to the overall success.

Example

“In my last project, I chose to implement a Bayesian approach for our predictive model because it allowed us to incorporate prior knowledge and update our predictions as new data came in. This flexibility was crucial given the dynamic nature of our data, and it ultimately led to more accurate forecasts.”

Technical Skills

6. Can you explain Bayesian statistics and its application in your work?

Understanding Bayesian statistics is important for a research scientist role, especially in data-driven decision-making.

How to Answer

Provide a brief overview of Bayesian statistics and discuss how you have applied it in your projects.

Example

“Bayesian statistics allows us to update our beliefs based on new evidence. In my previous role, I used Bayesian linear regression to model customer behavior, which provided us with a more nuanced understanding of the factors influencing purchasing decisions.”

7. Write a Python script to get all combinations from a list of numbers.

This question tests your coding skills and understanding of algorithms.

How to Answer

Explain your thought process for solving the problem and provide a high-level overview of your approach.

Example

“To generate all combinations from a list of numbers, I would use the itertools library in Python. I would import combinations from itertools and then iterate through the list to generate combinations of varying lengths, which can be done efficiently with a simple loop.”

8. Given a software installation table with user ID, what questions will you ask to check if there's an anomaly in the data?

This question evaluates your analytical skills and ability to identify data issues.

How to Answer

Discuss the types of anomalies you would look for and the questions you would ask to investigate further.

Example

“I would first check for duplicate user IDs or installations occurring in a very short time frame. I would also look for patterns in the data, such as unusually high installation rates from specific users or geographic locations, which could indicate fraudulent activity.”

9. How would you design a system to track user engagement metrics?

This question assesses your system design skills and understanding of user analytics.

How to Answer

Outline the key components of your design, including data collection, storage, and analysis.

Example

“I would design a system that collects user engagement data through event tracking in our application. This data would be stored in a centralized database, where I would implement ETL processes to clean and aggregate the data. Finally, I would use visualization tools to create dashboards that provide insights into user behavior over time.”

10. What statistical methods do you find most useful in your research?

This question allows you to showcase your knowledge of statistical techniques relevant to the role.

How to Answer

Discuss the statistical methods you frequently use and how they apply to your research.

Example

“I often use regression analysis to understand relationships between variables, as well as hypothesis testing to validate my findings. Additionally, I find clustering techniques useful for segmenting data and uncovering patterns that inform our strategies.”