23andMe Data Scientist Interview Questions + Guide in 2025

23andMe is a pioneering biotechnology company that provides genetic testing services to empower individuals with personalized health insights and ancestry information.

As a Data Scientist at 23andMe, you will play a crucial role in analyzing complex biological and genetic data to derive actionable insights that inform product development and improve user experience. Your key responsibilities will include designing and implementing statistical models, conducting data analysis, and collaborating with cross-functional teams to translate findings into strategic recommendations. The ideal candidate will possess strong programming skills, particularly in Python, and have a solid understanding of machine learning algorithms and statistical methodologies. A great fit for this role will demonstrate an ability to communicate complex concepts clearly and a passion for leveraging data to drive impactful decision-making in the context of health and genetics. Alignment with 23andMe's commitment to innovation and personalized healthcare is essential, as you will be contributing to a mission that seeks to empower individuals through data-driven insights.

This guide will equip you with the knowledge and confidence needed to navigate the interview process effectively, helping you showcase your technical skills and cultural fit within 23andMe.

The interview process for a Data Scientist at 23andMe is designed to assess both technical skills and cultural fit within the organization. It typically consists of several key stages:

1. Initial Phone Screen

The process begins with an initial phone screen, which usually lasts about 30 minutes. During this conversation, a recruiter will discuss the role and the company culture, while also gathering information about your background, skills, and career aspirations. This is an opportunity for you to express your interest in the position and to determine if 23andMe aligns with your professional goals.

2. Data Challenge

Following the initial screen, candidates are often required to complete a data challenge. This task is typically assigned about a week after the phone interview and is designed to evaluate your analytical skills and problem-solving abilities. The challenge may involve working with datasets to derive insights or build models, and it serves as a practical demonstration of your technical capabilities.

3. Onsite Interview

The final stage of the interview process is an onsite interview, which is a full-day event. This includes a series of one-on-one interviews with team members and stakeholders. Candidates are expected to present their past work in a 30-45 minute presentation, showcasing their experience and the impact of their projects. The onsite interviews are generally split between technical and cultural fit assessments, with half of the questions focusing on technical skills—such as whiteboarding Python algorithms and discussing relevant technical experiences from your resume—and the other half aimed at understanding how well you align with the company’s values and team dynamics.

As you prepare for your interview, it’s essential to be ready for the specific questions that may arise during these stages.

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

Understand the Company’s Mission and Values

23andMe is deeply committed to empowering individuals with genetic information to improve their health and well-being. Familiarize yourself with their mission, recent advancements in genetic research, and how data science plays a crucial role in their offerings. This knowledge will not only help you align your answers with the company’s goals but also demonstrate your genuine interest in their work.

Prepare for a Multi-Stage Interview Process

Expect a structured interview process that may include an initial phone screen, a data challenge, and an on-site interview. Be ready to showcase your technical skills through a data challenge that reflects real-world problems the company faces. Make sure to allocate sufficient time to prepare for each stage, as the interviewers appreciate candidates who can articulate their thought process clearly and effectively.

Showcase Your Past Projects

During the interview, you will likely be asked to walk through one of your past projects in detail. Choose a project that highlights your technical skills, problem-solving abilities, and how you’ve contributed to the success of the project. Be prepared to discuss the challenges you faced, the methodologies you employed, and the impact your work had on the team or organization.

Balance Technical and Cultural Fit

The on-site interview will likely include a mix of technical and cultural questions. While it’s essential to demonstrate your technical expertise—such as proficiency in Python and algorithm design—don’t overlook the importance of cultural fit. Be ready to discuss how your values align with 23andMe’s culture, emphasizing collaboration, innovation, and a passion for data-driven decision-making.

Practice Whiteboarding and Communication Skills

You may encounter whiteboarding exercises during the technical portion of the interview. Practice explaining your thought process clearly and concisely while solving problems on the board. This will not only showcase your technical skills but also your ability to communicate complex ideas effectively, which is crucial in a collaborative environment like 23andMe.

Be Ready for Behavioral Questions

Expect behavioral questions that assess how you handle challenges, work in teams, and adapt to change. Use the STAR (Situation, Task, Action, Result) method to structure your responses, providing concrete examples that illustrate your skills and experiences. This approach will help you convey your qualifications in a compelling manner.

Follow Up with Thoughtful Questions

At the end of the interview, you’ll likely have the opportunity to ask questions. Use this time to inquire about the team dynamics, ongoing projects, and how data science is shaping the future of 23andMe. Thoughtful questions not only demonstrate your interest but also help you gauge if the company is the right fit for you.

By following these tips and preparing thoroughly, you’ll position yourself as a strong candidate for the Data Scientist role at 23andMe. Good luck!

In this section, we’ll review the various interview questions that might be asked during a Data Scientist interview at 23andMe. The interview process will likely assess your technical skills, problem-solving abilities, and cultural fit within the company. Be prepared to discuss your past projects in detail, as well as demonstrate your proficiency in data analysis, machine learning, and statistical methods.

Experience and Background

1. Walk me through one of your past projects in detail.

This question allows you to showcase your experience and the impact of your work.

How to Answer

Choose a project that highlights your skills relevant to the role. Discuss the problem you were solving, the methods you used, and the results you achieved.

Example

“In my previous role, I worked on a project to predict customer churn using machine learning. I collected and cleaned the data, applied various algorithms, and ultimately implemented a logistic regression model that improved our retention strategy by 15%.”

Technical Skills

2. Can you explain the difference between supervised and unsupervised learning?

Understanding these concepts is fundamental for a Data Scientist.

How to Answer

Define both terms clearly and provide examples of when you would use each type of learning.

Example

“Supervised learning involves training a model on labeled data, where the outcome is known, such as predicting house prices. Unsupervised learning, on the other hand, deals with unlabeled data to find hidden patterns, like customer segmentation in marketing.”

3. Describe a time you had to use Python for a data analysis task.

This question assesses your practical experience with programming.

How to Answer

Discuss a specific instance where you utilized Python, focusing on the libraries and techniques you employed.

Example

“I used Python with Pandas and NumPy to analyze sales data for a retail client. I performed data cleaning, exploratory data analysis, and visualized the results using Matplotlib, which helped the client identify key trends in their sales performance.”

4. How do you handle missing data in a dataset?

This question tests your knowledge of data preprocessing techniques.

How to Answer

Explain the methods you use to address missing data and the rationale behind your choices.

Example

“I typically assess the extent of missing data first. If it’s minimal, I might use imputation techniques like mean or median substitution. For larger gaps, I consider removing those records or using predictive modeling to estimate the missing values.”

5. What is your experience with A/B testing?

A/B testing is crucial for data-driven decision-making.

How to Answer

Discuss your understanding of A/B testing and any relevant experience you have.

Example

“I have designed and analyzed several A/B tests to evaluate marketing strategies. For instance, I tested two different email campaigns and used statistical significance to determine which version led to higher conversion rates, ultimately guiding our marketing efforts.”

Cultural Fit

6. How do you prioritize your work when you have multiple projects with tight deadlines?

This question evaluates your time management and prioritization skills.

How to Answer

Describe your approach to managing competing priorities and ensuring quality work.

Example

“I prioritize my tasks based on urgency and impact. I use project management tools to track deadlines and communicate with my team to ensure alignment. This approach helped me successfully deliver multiple projects on time without compromising quality.”

7. Describe a situation where you had to collaborate with a cross-functional team.

Collaboration is key in a data-driven environment.

How to Answer

Share an example that highlights your teamwork and communication skills.

Example

“I collaborated with the marketing and product teams to analyze user feedback data. By facilitating regular meetings and sharing insights, we were able to align our strategies and improve the product based on user needs, resulting in a 20% increase in user satisfaction.”

8. How do you stay updated with the latest trends in data science?

This question assesses your commitment to continuous learning.

How to Answer

Discuss the resources you use to keep your skills sharp and stay informed.

Example

“I regularly read industry blogs, attend webinars, and participate in online courses. I also engage with the data science community on platforms like LinkedIn and GitHub to exchange ideas and learn from others’ experiences.”

9. What values do you think are important for a data scientist at 23andMe?

Understanding the company culture is essential for a good fit.

How to Answer

Reflect on the company’s mission and values, and relate them to your own.

Example

“I believe values such as integrity, curiosity, and collaboration are vital for a data scientist at 23andMe. Upholding ethical standards in data handling and fostering a collaborative environment aligns with my personal values and enhances the quality of our work.”