Nomura Data Scientist Interview Questions + Guide in 2025

Nomura is an Asia-headquartered financial services group that connects markets East and West, offering a broad range of services to individuals, institutions, corporations, and governments through its diverse business divisions.

As a Data Scientist at Nomura, you will play a pivotal role in the Quantitative Investment Team, focusing on the development and maintenance of quantitative models, conducting research, and providing valuable insights that inform investment strategies. Key responsibilities include analyzing and interpreting complex datasets, identifying trends that can drive investment decisions, and collaborating with team members to prioritize investment opportunities and risks. The ideal candidate will possess strong programming skills in Python or R, experience with statistical modeling and machine learning techniques, and a solid understanding of financial markets and investment concepts. Nomura values self-starters who are passionate about data science and investment research, and who can thrive in a collaborative and innovative environment.

This guide is designed to help you prepare effectively for your interview at Nomura, equipping you with insights into the role and the skills required to stand out as a strong candidate.

The interview process for a Data Scientist role at Nomura is structured and thorough, designed to assess both technical and behavioral competencies. It typically consists of multiple rounds, each focusing on different aspects of the candidate's qualifications and fit for the role.

1. Initial Screening

The process begins with an initial screening, which is often a phone interview with a recruiter or hiring manager. This conversation is generally focused on understanding your background, motivations for applying to Nomura, and your fit within the company culture. Expect questions about your previous experiences and how they relate to the role you are applying for.

2. Technical Interviews

Following the initial screening, candidates usually undergo two to three technical interviews. These sessions are designed to evaluate your proficiency in key areas such as statistics, probability, algorithms, and programming languages like Python. You may be asked to solve problems related to data analysis, statistical modeling, and machine learning techniques. Additionally, expect questions that assess your understanding of financial markets and investment concepts, as these are crucial for the role.

3. Behavioral Interviews

In parallel with the technical assessments, candidates will also participate in behavioral interviews. These interviews focus on your past experiences, problem-solving abilities, and how you handle challenging situations. Interviewers may ask you to describe specific instances where you demonstrated analytical thinking, teamwork, and effective communication skills. This part of the process is essential for determining how well you align with Nomura's values and work environment.

4. Final Interview

The final stage typically involves a wrap-up interview with senior team members or management. This session may include a mix of technical and behavioral questions, as well as discussions about your long-term career aspirations and how they align with the goals of the team and the company. This is also an opportunity for you to ask questions about the team dynamics, projects, and expectations.

As you prepare for your interviews, it's important to be ready for a variety of questions that will test both your technical knowledge and your ability to work collaboratively in a fast-paced environment. Here are some of the types of questions you might encounter during the interview process.

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

Understand the Financial Landscape

Given Nomura's focus on financial services, it's crucial to familiarize yourself with current economic trends and market conditions. Be prepared to discuss how these factors influence investment strategies. This knowledge will not only demonstrate your interest in the role but also your ability to apply data science in a financial context.

Prepare for Behavioral Questions

Nomura places a strong emphasis on cultural fit and teamwork. Expect behavioral questions that assess your past experiences and how they align with the company's values. Use the STAR (Situation, Task, Action, Result) method to structure your responses, focusing on your contributions to team projects and how you overcame challenges.

Brush Up on Technical Skills

As a Data Scientist, you will need to showcase your proficiency in statistics, probability, and programming languages like Python. Be prepared to solve problems related to data analysis, statistical modeling, and algorithms during the technical rounds. Practice coding challenges that involve data manipulation and statistical calculations, as these are likely to come up.

Showcase Your Projects

Be ready to discuss your previous projects in detail, especially those that involved quantitative modeling or data analysis. Highlight your role, the tools you used, and the impact of your work. This will not only demonstrate your technical skills but also your ability to apply them in real-world scenarios.

Communicate Clearly and Confidently

Effective communication is key at Nomura. During your interview, articulate your thoughts clearly and confidently. When discussing technical concepts, ensure that you explain them in a way that is understandable, even to those who may not have a technical background. This will showcase your ability to collaborate with diverse teams.

Be Ready for a Multi-Round Process

The interview process at Nomura can involve multiple rounds, including technical and HR interviews. Stay organized and be prepared for each stage. If you encounter challenging questions, take a moment to think before responding. It's better to provide a well-thought-out answer than to rush.

Embrace the Company Culture

Nomura values innovation and ownership. Show your enthusiasm for contributing new ideas and solutions. Be prepared to discuss how you can bring a fresh perspective to the team and how your background aligns with the entrepreneurial spirit of the company.

Follow Up

After your interview, consider sending a thank-you email to express your appreciation for the opportunity. This not only reinforces your interest in the position but also leaves a positive impression on your interviewers.

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

In this section, we’ll review the various interview questions that might be asked during a data scientist interview at Nomura. The interview process will likely assess a combination of technical skills, statistical knowledge, and behavioral competencies. Candidates should be prepared to discuss their experience with data analysis, quantitative modeling, and their understanding of financial markets.

Technical Skills

1. Explain the concept of feature engineering and its importance in model development.

Understanding feature engineering is crucial as it directly impacts the performance of your models.

How to Answer

Discuss how feature engineering involves selecting, modifying, or creating new features from raw data to improve model accuracy. Emphasize its role in transforming data into a format that better represents the underlying problem.

Example

“Feature engineering is the process of using domain knowledge to select or create features that enhance the predictive power of a model. For instance, in a financial dataset, creating a feature that captures the volatility of stock prices can significantly improve the model's ability to predict future price movements.”

2. How would you evaluate the performance of a machine learning model?

This question tests your understanding of model evaluation metrics.

How to Answer

Mention various metrics such as accuracy, precision, recall, F1 score, and ROC-AUC, and explain when to use each based on the problem context.

Example

“To evaluate a machine learning model, I would use metrics like accuracy for balanced datasets, precision and recall for imbalanced datasets, and the F1 score to balance both. Additionally, I would consider ROC-AUC for binary classification problems to assess the model's ability to distinguish between classes.”

3. Can you describe a time when you had to clean and preprocess a large dataset?

This question assesses your practical experience with data preparation.

How to Answer

Provide a specific example that highlights your approach to data cleaning, including handling missing values, outliers, and data normalization.

Example

“In my previous role, I worked with a large financial dataset that had numerous missing values and outliers. I used imputation techniques for missing values and applied z-score normalization to handle outliers, ensuring the data was suitable for analysis and modeling.”

4. What statistical methods do you commonly use in your analysis?

This question gauges your statistical knowledge relevant to data science.

How to Answer

Discuss methods such as regression analysis, hypothesis testing, and time series analysis, and explain their applications in financial contexts.

Example

“I frequently use regression analysis to identify relationships between variables, hypothesis testing to validate assumptions, and time series analysis for forecasting stock prices. These methods help in making data-driven investment decisions.”

5. Describe a project where you used Python for data analysis.

This question evaluates your programming skills and practical application of data science.

How to Answer

Outline a specific project, detailing the libraries used, the analysis performed, and the insights gained.

Example

“I worked on a project analyzing historical stock prices using Python’s Pandas and NumPy libraries. I performed time series analysis to identify trends and seasonality, which helped the investment team make informed decisions about future investments.”

Behavioral Questions

1. Why do you want to work at Nomura?

This question assesses your motivation and alignment with the company’s values.

How to Answer

Express your interest in Nomura’s global reach and commitment to innovation in financial services.

Example

“I am drawn to Nomura because of its strong reputation in the financial services industry and its commitment to innovation. I believe my skills in data science can contribute to developing cutting-edge investment strategies that align with Nomura’s goals.”

2. Can you describe a challenging situation you faced in your previous role and how you handled it?

This question evaluates your problem-solving and resilience.

How to Answer

Share a specific challenge, your approach to resolving it, and the outcome.

Example

“In a previous role, I faced a challenge when a key dataset was corrupted just before a major analysis deadline. I quickly collaborated with the IT team to recover the data and implemented a backup strategy to prevent future occurrences. This experience taught me the importance of data integrity and proactive planning.”

3. How do you prioritize your workload when managing multiple projects?

This question assesses your organizational skills and ability to multitask.

How to Answer

Discuss your approach to prioritization, such as using project management tools or techniques like the Eisenhower Matrix.

Example

“I prioritize my workload by assessing project deadlines and impact. I use project management tools like Trello to track progress and ensure that I focus on high-impact tasks first. This approach helps me manage multiple projects effectively without compromising quality.”

4. Describe a time when you had to work with a diverse team. How did you ensure effective collaboration?

This question evaluates your teamwork and communication skills.

How to Answer

Highlight your experience working in multicultural teams and your strategies for fostering collaboration.

Example

“I worked on a project with team members from different cultural backgrounds. I facilitated regular check-ins to ensure everyone was aligned and encouraged open communication. This approach helped us leverage our diverse perspectives to enhance the project outcomes.”

5. How do you stay updated with the latest trends in data science and finance?

This question assesses your commitment to continuous learning.

How to Answer

Mention specific resources, such as online courses, webinars, or industry publications that you follow.

Example

“I stay updated by following industry publications like the Financial Times and attending webinars on data science trends. I also participate in online courses on platforms like Coursera to enhance my skills and knowledge in both data science and finance.”