Top 7 ByteDance Data Scientist Interview Questions + Guide in 2025

ByteDance Ltd. is a Chinese multinational tech company that developed the Toutiao (“Headlines”) content platform, formerly a news recommendation engine, and TikTok, the video-sharing social network service. Over the years, Tiktok has soared in popularity, and according to a 2024 report, the app currently has over 1.04 billion active users worldwide, with over four billion downloads globally on app stores and Google Play. One important feature of TikTok is its “machine learning-backed recommendation engine,” which is a hot topic within the data science community.

TikTok’s recommendation system is user-centric, using advanced AI to collect user data and create tailored recommendations. It begins with cold-start adjustments and gradually evolves to provide explicit recommendations for active users.

This guide offers insights into the interview process and key Bytedance interview questions you need to be prepared for if you’re aiming for this role.

ByteDance is shaping the way AI changes our lives, and data scientists are at the forefront of this journey. Data scientists, data engineers, and data analysts form the core data structure at this company and are responsible for bridging the gap between data and sound business decision-making. Data scientist roles at ByteDance can range from basic data analytics methods, such as data analysis, hypothesis testing, A/B testing, experimentation, data visualization, and presentation, etc., to more advanced machine learning and deep learning techniques such as regression, classifications, clustering, etc.

Required Skills

As a company that prides itself as a leading body in AI technology, ByteDance takes only the best. Candidates applying for the data scientist role should possess at least three years of industry experience doing quantitative analysis or any other data analytics-related role.

Other basic requirements include:

• Bachelor’s or Master’s degree in Computer Science, Information Systems, Electrical Engineering, Physics, Mathematics, Statistics, Economics, or other quantitative fields.
• Hands-on experience with SQL, ETL, or at least with one of the scripting languages, e.g., Python, Java, R, Scala, Go, C++.
• Experience with statistical software such as R, MATLAB, Python, pandas, Tableau, etc.
• Experience with statistical data analysis such as linear models, multivariate analysis, stochastic models, sampling methods, hypothesis testing, model evaluation (regression, decision trees, k-means, etc.), and common regression and classification algorithms.
• Hands-on experience handling large datasets and analytical tools such as Hive, Spark, etc.
• Experience with predictive analytics, statistics, and machine learning techniques and algorithms.
• Experience with a data visualization tool (e.g., Mode Analytics/Chartio/Tableau).

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

Prepare for a Fast-Paced Process

ByteDance is known for its quick interview turnaround. Be ready to move swiftly through the stages, as candidates often report receiving feedback within days. Ensure your resume is polished and that you can articulate your experiences clearly and concisely. Familiarize yourself with the role's requirements and be prepared to discuss how your background aligns with ByteDance's mission and values.

Master the Language Requirement

Given that many interviews are conducted in Mandarin, it’s crucial to be proficient in the language, especially if it’s your first language. If you are not a native speaker, practice technical vocabulary and common phrases related to data science in Mandarin. This will not only help you communicate effectively but also demonstrate your commitment to the role and the company culture.

Focus on Technical Proficiency

Expect a strong emphasis on technical skills, particularly in Python, SQL, and machine learning concepts. Brush up on your knowledge of algorithms, data structures, and statistical methods. Be prepared to solve coding problems on the spot, as many candidates report facing LeetCode-style questions. Practicing these types of problems will help you feel more confident during the technical interviews.

Showcase Your Problem-Solving Skills

ByteDance values candidates who can think critically and approach problems creatively. During the interview, be prepared to discuss your thought process when tackling complex problems. Use the STAR (Situation, Task, Action, Result) method to structure your responses, especially when discussing past projects or challenges you've faced.

Understand the Company Culture

ByteDance emphasizes collaboration, innovation, and a willingness to challenge the status quo. Familiarize yourself with the company's products and recent developments, particularly in the realm of security and risk management. Demonstrating an understanding of how your role contributes to the company's mission will set you apart from other candidates.

Prepare for Behavioral Questions

Expect behavioral questions that assess your fit within the company culture. Reflect on your past experiences and how they align with ByteDance's values of creativity and teamwork. Be ready to discuss how you handle ambiguity, work in cross-functional teams, and adapt to fast-paced environments.

Be Ready for Case Studies

Candidates often encounter case questions related to statistical analysis and A/B testing. Brush up on your knowledge of experimental design and be prepared to discuss how you would approach a case study relevant to risk management or data mining. This will demonstrate your analytical skills and ability to apply theoretical knowledge to real-world scenarios.

Follow Up with Insightful Questions

At the end of the interview, take the opportunity to ask thoughtful questions about the team, projects, and company culture. This not only shows your interest in the role but also helps you gauge if ByteDance is the right fit for you. Consider asking about the challenges the team is currently facing or how success is measured in the role.

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

The ByteDance data science team boasts a wide range of products and content services across a wide array of languages and cultures and, as such, possesses a large number of departments and teams. Data scientists work within the data science team and cross-functionally with other internal teams on new and existing ByteDance products and improving user experiences. Depending on the assigned team, specific roles can vary and may be tailored specifically to particular projects.

Listed below are some of the data science teams at ByteDance and specific data scientist roles within that team:

• Business Platform: Building business service platforms for core internal business, providing business/technical solutions in critical areas, working with large and complex data to solve difficult, non-routine analysis problems, and applying advanced analytics methods to provide insight from data. Other responsibilities can involve developing and conducting analysis, forecasting, and optimization methods to improve Bytedance’s core products, such as payment, game, and growth.
• Game Strategy: Conducting analysis, including building and managing Business Intelligence (BI) reporting to monitor business growth and designing models to predict growth trends, and collaborating with PMO to design and implement project management (PM) processes to enforce data-driven decisions.
• Research and Design (R&D) Networking: Developing a scalable data pipeline for the collection and aggregation of network system data, such as network resource usage, traffic statistics, device operation status, etc., and making this data universally available for both real-time and retrospective analysis use. Roles also involve developing analytical models for extracting insights from network events and making recommendations based on results from such analysis.
• Global Security Architecture: Focusing on corporate security, risk, and technical privacy strategy and research prioritization, applying security analytics using big data, machine learning, and artificial intelligence (AI), working with cutting-edge cyber security technology to develop models that will recognize patterns, changes, deviations, and hidden insights, to drive defense decisions and strategy against advanced cyber threats. Other basic roles in this team include developing robust data collection processes, ensuring data quality and integrity, building predictive models, and interpreting data analysis results.
• R&D Machine Learning: Developing tools and processes to analyze from ByteDance database, developing an efficient and robust A/B testing framework, building custom models and algorithms to apply to data sets, testing model quality, and performance, and utilizing predictive modeling to optimize customer experiences, generate revenue, and drive growth. Functions also include teaming up with internal teams, especially engineers, to implement models, monitor results, and design learning solutions.
• Analytics, Trust & Safety (TikTok): Leveraging data to identify trends, conducting root cause analysis for insights, developing metrics to evaluate risks, developing dashboards for risk detection, and conveying the results across multi-level organizations and stakeholders through data-driven recommendations.
• TikTok Ads Platform: Building and prototyping analysis pipelines to provide scalable insights, developing metrics, and leveraging TikTok’s large and complex data to solve difficult and non-routine problems.
• User Growth (TikTok): Building and analyzing dashboards and reports, evaluating and defining metrics, managing performance marketing models, partnering with engineering teams on areas of scalability and performance optimization, and collaborating with stakeholders to understand business problems.

The interview process for a Data Scientist role at Bytedance Inc. is structured and typically consists of multiple rounds, focusing on both technical and behavioral aspects. Candidates can expect a thorough evaluation of their skills and experiences relevant to data science, particularly in the context of risk management and machine learning.

1. Initial Application and Screening

The process begins with the submission of an online application, followed by an initial screening call with a recruiter. This call usually lasts around 30 minutes and serves to assess the candidate's background, motivations, and fit for the company culture. The recruiter may also discuss the role's expectations and the candidate's relevant experiences.

2. Online Assessment

Candidates who pass the initial screening are typically invited to complete an online coding assessment. This assessment usually consists of several coding problems that test the candidate's proficiency in programming languages such as Python and SQL, as well as their understanding of algorithms and data structures. The assessment is often time-constrained, requiring candidates to demonstrate their problem-solving skills under pressure.

3. Technical Interviews

Following the online assessment, candidates will undergo a series of technical interviews, usually three rounds. These interviews are conducted by senior data scientists or team leads and focus on various technical topics, including machine learning algorithms, statistical analysis, and data mining techniques. Candidates should be prepared to discuss their previous projects in detail and may be asked to solve problems in real-time, demonstrating their analytical thinking and coding abilities.

4. Behavioral Interview

In addition to technical interviews, candidates will also participate in a behavioral interview. This round assesses the candidate's soft skills, such as communication, teamwork, and adaptability. Interviewers may ask about past experiences, challenges faced, and how the candidate aligns with Bytedance's mission and values.

5. Final Interview with HR

The final step in the interview process is typically a conversation with an HR representative. This interview may cover logistical details such as salary expectations, benefits, and company culture. It also provides an opportunity for candidates to ask any remaining questions they may have about the role or the company.

Candidates should be aware that proficiency in Mandarin may be required for some positions, and the interview process may be conducted in Mandarin, depending on the team and role.

As you prepare for your interview, it's essential to familiarize yourself with the types of questions that may be asked during the process.

The ByteDance data science interview questions feature standardized questions tailored to specific roles, and the scope of the interview covers the length and breadth of data science, as well as leadership quality and product sense.

An important tip is to read up on the company’s mission and its six core values. Structure your answers and responses around one or more core values, especially when you are talking about yourself and the projects you’ve done in the past.

Common questions will be tied around statistics, especially probability (both joint and conditional), central limit theorem, distributions (including exponential, geometric, and binomial), etc., experimental design, SQL, and some machine learning techniques, such as regression, classification algorithms, clustering, etc.

A strong foundation in statistics and probability, A/B testing, experimentation, etc., is necessary to ace the ByteDance Data Scientist interview, so remember to brush up on your knowledge of these topics.

1. If you were the data manager for a product and responsible for providing ten metrics to the CEO every day, what metrics would you choose?
2. A company has introduced a new feature for a product for a month. How do you evaluate the feature?
3. What single metric would you use to measure how well a new app is doing?
4. How do you make a trade-off between quality and cost?
5. Tell me about a time when you relentlessly worked on improving the quality of an already working product or service.
6. Given a string str, write a function perm_palindrome to determine whether there exists a permutation of str that is a palindrome.
7. We’re given a table of bank transactions with three columns: user_id, a deposit or withdrawal value (determined if the value is positive or negative), and created_at time for each transaction. Write a query to get the total three-day rolling average for deposits by day.

See more ByteDance data scientist questions from Interview Query: