The questions below represent the types of challenges you will face during the Betterup interview process. They are designed to test both your technical depth and your ability to apply scientific thinking to real-world product scenarios.

Technical & Statistical Questions

These questions assess your foundational knowledge of statistics and your ability to manipulate data.

• Walk me through how you would conduct a power analysis for a new behavioral intervention.
• How do you handle outliers in a dataset measuring user engagement?
• Write a function in R to calculate the rolling average of user assessment scores over a 30-day window.
• Explain the difference between fixed and random effects in a mixed-effects model.
• How would you test if a newly introduced product feature caused a statistically significant increase in user retention?

Study Design & Applied Research

These questions test your ability to structure scientific inquiries around Betterup's specific product offerings.

• Design a study to validate the effectiveness of a new coaching methodology for enterprise managers.
• If we want to use an LLM to summarize coaching sessions, how would you design a research plan to ensure the summaries are accurate and unbiased?
• How would you measure the long-term impact of a 6-week mental fitness program?
• What are the risks of using self-reported survey data to measure behavioral change, and how do you mitigate them?
• Design an A/B test for a new onboarding flow. What are your primary and secondary metrics?

Behavioral & Mission Alignment

These questions evaluate your cultural fit and your passion for the work.

• Why are you passionate about the science of coaching and human transformation?
• Tell me about a time your research findings contradicted the assumptions of a product team. How did you handle it?
• Where do you see your research interests taking you in the next few years?
• Describe a time you had to explain a complex statistical concept to an executive with no technical background.
• How do you prioritize your research initiatives when working in a fast-paced, ambiguous startup environment?

Programming & Tooling (R)

Your technical execution will be heavily scrutinized, specifically your proficiency in R. Betterup relies on R for much of its data analysis and statistical modeling. Strong candidates write clean, reproducible, and well-documented code.

Be ready to go over:

• Data Wrangling – Using the tidyverse (dplyr, tidyr) to clean and transform messy datasets.
• Data Visualization – Creating clear, compelling charts using ggplot2 to communicate findings.
• Statistical Implementation – Running models and extracting insights using base R or specialized packages.
• Reproducibility – Structuring your code and using RMarkdown to create shareable reports.

Example questions or scenarios:

• "Given this raw dataset of user interactions, write a dplyr pipeline to aggregate the average session length by user cohort."
• "How would you visualize the distribution of coaching scores across different demographic groups?"
• "Write an R script to run a mixed-effects model accounting for the variance between different enterprise clients."

Mission Alignment & Future Vision

Betterup has a distinct, highly mission-driven culture. Interviewers, especially hiring managers and executives, want to know that you are deeply invested in the concept of human transformation. Strong performance in this area means speaking authentically about your passions and demonstrating how your career goals align with the company's trajectory.

Be ready to go over:

• Personal Motivations – Why you care about coaching, mental fitness, or behavioral science.
• Adaptability – Your willingness to explore new, unconventional research avenues (like testing GPT applications).
• Communication Style – Your ability to engage in deep, sometimes philosophical conversations about human potential.

Example questions or scenarios:

• "Where do you see yourself and your research passions evolving in the next five years?"
• "Tell me about a time you had to pivot your research focus due to changing business priorities."
• "Why are you passionate about the specific mission of Betterup?"

6. Key Responsibilities

As a Research Scientist at Betterup, your day-to-day work will be a mix of deep-focus analytical tasks and highly collaborative strategic planning. You will be responsible for designing and executing behavioral studies that validate the effectiveness of the Betterup platform. This involves taking raw, complex data generated by thousands of coaching sessions and transforming it into clear narratives about human growth.

A significant portion of your time will be spent writing code, primarily in R, to clean data, run statistical models, and build visualizations. You will work closely with the engineering and data infrastructure teams to ensure the data you need is accessible and reliable. You will also partner directly with product managers, translating your scientific findings into recommendations for new features or interventions.

Furthermore, you will act as an internal consultant for innovation. The Labs team frequently explores emerging technologies. You may find yourself designing frameworks to test how large language models (like GPT) can be safely and effectively integrated into the coaching experience. This requires a flexible mindset, as you will balance rigorous, traditional behavioral research with fast-paced, exploratory tech validation.

7. Role Requirements & Qualifications

To be highly competitive for the Research Scientist position, you must bring a strong blend of academic rigor and practical data science experience.

• Must-have skills – Deep proficiency in R (specifically tidyverse and ggplot2); a strong foundation in statistics (hypothesis testing, regression, mixed models); proven experience in end-to-end study design (experimental and observational); and excellent communication skills to translate science to business leaders.
• Must-have experience – An advanced degree (Ph.D. or highly specialized Master's) in a quantitative behavioral science field (Psychology, Cognitive Science, Economics, etc.), plus industry experience applying research methodologies to product or business problems.
• Nice-to-have skills – Familiarity with SQL and Python; experience with natural language processing (NLP) or evaluating LLM outputs; a background in psychometrics or survey validation.
• Nice-to-have experience – Previous tenure at a fast-growing startup; experience working directly with product and engineering teams in an agile environment.

8. Frequently Asked Questions

Q: How difficult is the take-home assignment? The take-home assignment is known to be rigorous and time-consuming. While you may be told it takes 5-6 hours, many candidates report spending significantly longer (up to 15-18 hours) to ensure the code is flawless, the data analysis is deep, and the study design is comprehensive. Plan your schedule accordingly.

Q: Why is there an interview with a senior executive? Betterup places a massive premium on mission alignment and cultural fit. The core team is tight-knit, and executives want to ensure that every senior hire, especially in a strategic role like a Research Scientist, shares the company's vision for human transformation and can thrive in their specific corporate culture.

Q: Will I be tested on Python or SQL? While SQL and Python are valuable, the core technical evaluations for this specific role heavily index on R. You should be fully prepared to write live code and complete your take-home data analysis using R and its associated packages (like tidyverse).

Q: What kind of research does the team actually do? The research blends traditional behavioral science (measuring the efficacy of coaching, psychometric validation) with innovative product testing. Recently, this has included exploring how emerging AI technologies, such as GPT models, can be applied to enhance or scale coaching frameworks.

Q: How fast is the interview timeline? The initial stages (hiring manager screen and technical screen) usually move very quickly, often within a couple of weeks. However, scheduling the virtual onsite and executive rounds can sometimes face delays due to internal startup dynamics and executive availability.

9. Other General Tips

• Timebox but polish the take-home: Because the take-home assignment is a critical differentiator, do not rush it. Even if it takes longer than the suggested time, ensure your R code is impeccably clean, heavily commented, and that your final report reads like a polished internal memo.
• Embrace the mission-driven language: Betterup has a distinct culture that heavily emphasizes pursuing passions and personal growth. Do not shy away from speaking earnestly about your personal mission and why you care about human well-being.
• Prepare for ambiguity: You may be asked questions about applying research to highly ambiguous areas, such as testing GPT chatbots. Show that you can apply rigorous scientific frameworks even to unproven, cutting-edge technologies.