10X Genomics is an innovative biotech company at the forefront of advanced genetic research and bioinformatics. Their mission is to accelerate genetic discovery and empower scientific advancements that improve human health. As a Data Scientist at 10X Genomics, you will leverage cutting-edge technologies to analyze complex biological data, develop computational models, and derive insights that drive scientific research and product development.

Excelling in this role requires a solid foundation in statistics, machine learning, and bioinformatics, as well as a strong ability to interpret and communicate complex data. Candidates should be prepared for a challenging yet rewarding interview process that assesses both technical expertise and problem-solving skills.

If you're passionate about working at the intersection of technology and biology, this position at 10X Genomics could be the perfect fit for you. Dive into this guide to get a comprehensive understanding of the interview process, commonly asked questions, and valuable tips for success. Let's get started!

Submitting Your Application

The first step is to submit a compelling application that reflects your technical skills and interest in joining 10X Genomics as a Data Scientist. Whether you were contacted by a recruiter from 10X Genomics or have taken the initiative yourself, carefully review the job description and tailor your CV according to the prerequisites.

Tailoring your CV may include identifying specific keywords that the hiring manager might use to filter resumes and crafting a targeted cover letter. Furthermore, don’t forget to highlight relevant skills and mention your work experiences.

Recruiter/Hiring Manager Call Screening

If your CV happens to be among the shortlisted few, a recruiter from the Talent Acquisition Team at 10X Genomics will make contact and verify key details like your experiences and skill level. Behavioral questions may also be a part of the screening process.

In some cases, the hiring manager for the Data Scientist role might be present during the screening round to answer your queries about the role and the company itself. They may also indulge in surface-level technical and behavioral discussions.

The whole recruiter call should take about 30 minutes.

Technical Virtual Interview

Successfully navigating the recruiter round will present you with an invitation for the technical screening round. Technical screening for the Data Scientist role at 10X Genomics is usually conducted through virtual means, including video conference and screen sharing. Questions in this 1-hour long interview stage may revolve around the company's data systems, ETL pipelines, SQL queries, and biological data analysis.

Take-home assignments regarding product metrics, analytics, and data visualization are common for data scientist roles. Apart from these, your proficiency in hypothesis testing, probability distributions, and machine learning fundamentals may also be assessed during the round.

Depending on the seniority of the position, case studies and similar real-scenario problems may also be assigned.

Onsite Interview Rounds

Followed by a second recruiter call outlining the next stage, you’ll be invited to attend the onsite interview loop. Multiple interview rounds, varying with the role, will be conducted during your day at the 10X Genomics office. Your technical prowess, including programming and ML modeling capabilities, will be evaluated against the finalized candidates throughout these interviews.

If you were assigned take-home exercises, a presentation round may also await you during the onsite interview for the Data Scientist role at 10X Genomics.

Quick Tips For 10X Genomics Data Scientist Interviews

You should plan to brush up on any technical skills and try as many practice interview questions and mock interviews as possible. A few tips for acing your 10X Genomics interview include:

• Understand Biological Data: Given 10X Genomics is heavily involved in biological research and innovation, ensure you are well-versed in analyzing biological datasets and understanding the domain-specific challenges.
• Master Data Science Fundamentals: Be prepared to answer questions related to statistics, machine learning, and data visualization. Practical knowledge and the ability to apply these fundamentals to real-world problems are crucial.
• Showcase Problem-Solving Skills: 10X Genomics looks for candidates who can approach problems methodically. Demonstrating structured problem-solving skills and the ability to employ critical thinking can set you apart.

Typically, interviews at 10X Genomics vary by role and team, but commonly Data Scientist interviews follow a fairly standardized process across these question topics.

• Write a function calculate_rmse to calculate the root mean squared error of a regression model. The function should take in two lists, one that represents the predictions y_pred and another with the target values y_true.

• Write a query to get the last transaction for each day from a table of bank transactions. Given a table of bank transactions with columns id, transaction_value, and created_at, write a query to get the last transaction for each day. The output should include the id of the transaction, datetime of the transaction, and the transaction amount. Order the transactions by datetime.

• Write a function random_key that returns a key at random with a probability proportional to the weights. Given a dictionary with weights, write a function random_key that returns a key at random with a probability proportional to the weights.

• Write a function to get a sample from a standard normal distribution. Create a function to generate a sample from a standard normal distribution.

• Write an efficient function nearest_entries to find the closest element to N in a sorted list and return surrounding elements. Given a sorted list of integers ints with no duplicates, write an efficient function nearest_entries that takes in integers N and k and finds the element closest to N, returning that element along with the k-next and k-previous elements of the list.

• How would you analyze the churn behavior of users on different Netflix pricing plans? Netflix has two pricing plans: $15/month or $100/year. An executive wants to understand the churn behavior of users on these plans. What metrics, graphs, and models would you build to provide an overarching view of subscription performance?

• How would you predict which merchants DoorDash should acquire in a new market? As a data scientist at DoorDash, you need to build a model to predict which merchants the company should target for acquisition when entering a new market. How would you approach this task?

• How would you value the benefit of keeping a hit TV show on Netflix? Netflix executives are considering renewing a deal with another TV network for exclusive streaming rights to a hit TV series. The show has been on Netflix for a year. How would you approach valuing the benefit of keeping this show on Netflix?

• How would you measure and address the success of LinkedIn’s newsfeed ranking algorithm?

• How would you measure the success of LinkedIn’s newsfeed ranking algorithm?

• If some success metrics for the newsfeed algorithm are increasing while others are decreasing, how would you approach this situation?

• How would you determine the statistical significance of an AB test for a landing page redesign? You want to launch a redesign of a landing page to improve the click-through rate using an AB test. How would you infer if the results of the click-through rate were statistically significant or not?

• How would you explain what a p-value is to someone who is not technical? Explain the concept of a p-value in simple terms to a non-technical person. Focus on its role in hypothesis testing and what it indicates about the results.

• How many more samples would we need to decrease the margin of error from 3 to 0.3? Given a sample size (n) with a margin of error of 3, calculate the additional number of samples required to reduce the margin of error to 0.3.

• How would you determine if the results of an AB test on click-through rate are statistically significant? Describe the process of analyzing AB test results to determine if the observed differences in click-through rates are statistically significant. Include steps such as hypothesis testing and p-value interpretation.

• How would you build a model to predict which merchants DoorDash should acquire in a new market? As a data scientist at DoorDash, how would you develop a model to identify which merchants the company should target for acquisition when entering a new market?

• How would you assign point values to letters in a Spanish Scrabble game without knowing Spanish? If you need to build Scrabble for Spanish users and don't know Spanish, how would you determine the point values for each letter?

What is the average salary for a Data Scientist at 10X Genomics?

Q: What is the interview process like for a Data Scientist position at 10X Genomics? The interview process at 10X Genomics typically includes several stages: an initial recruiter call, a technical screening, a coding challenge, and onsite interviews. The onsite interviews often include technical interviews, case studies, and discussions revolving around your past experiences and projects.

Q: What kind of technical questions can I expect during the interview at 10X Genomics? You can expect technical questions that cover a range of topics like statistical modeling, data analysis, and machine learning. Additionally, there are coding questions that test your proficiency in languages such as Python or R. It's a good idea to use Interview Query to practice these types of questions and get familiar with the format.

Q: What skills are required for a Data Scientist at 10X Genomics? To thrive as a Data Scientist at 10X Genomics, you need strong analytical skills, expertise in statistical modeling, and proficiency in programming languages like Python and R. Equally important is the ability to interpret complex biological data and collaborate effectively with cross-functional teams.

Q: What is the company culture like at 10X Genomics? 10X Genomics fosters a collaborative and innovative culture that values continuous learning and cross-disciplinary teamwork. The company encourages employees to tackle challenging problems and supports a culture of mutual respect and intellectual curiosity.

Q: How can I prepare for an interview at 10X Genomics? Preparation for 10X Genomics’ interview involves conducting in-depth research about the company and its cutting-edge technologies. Additionally, practice common interview questions and refine your technical skills using Interview Query. Preparing case studies showcasing your problem-solving abilities and contributions to past projects can also be highly beneficial.

Embarking on a journey to secure the Data Scientist position at 10X Genomics is a promising adventure that blends cutting-edge science with data expertise. For more detailed insights and tailored preparation tips, check out our comprehensive 10X Genomics Interview Guide. We’ve also crafted guides for other roles like software engineer and data analyst, helping you understand the unique nuances of 10X Genomics' interview process across different positions.

At Interview Query, we equip you with a wealth of resources, empowering you with the knowledge, confidence, and strategic insights needed to excel in your interview journey. Explore all our company interview guides for a well-rounded preparation experience, and feel free to reach out if you have any questions.

Good luck with your interview, and get ready to make your mark at 10X Genomics!