MSD Data Scientist Interview Questions + Guide in 2025

MSD is a global leader in the pharmaceutical industry, dedicated to improving health and well-being through innovative medicines and vaccines.

As a Data Scientist at MSD, you will play a pivotal role in leveraging data to drive insights and support decision-making processes across the organization. Your key responsibilities will include designing and implementing data models and algorithms, analyzing large datasets to uncover trends and patterns, and collaborating with cross-functional teams to solve complex business problems. You will be expected to have strong skills in statistical analysis, machine learning, and programming languages such as Python or R. Additionally, experience with data visualization tools and a solid understanding of data engineering principles will set you apart as a candidate.

The ideal candidate will not only demonstrate technical proficiency but also possess strong problem-solving abilities, excellent communication skills, and an adaptability to work in a dynamic environment. As MSD values collaboration and innovation, a candidate's ability to work well in diverse teams and their willingness to embrace new ideas will be crucial for success in this role.

This guide is designed to equip you with the knowledge and insights necessary to navigate the interview process effectively, enabling you to present yourself as a strong candidate who aligns with MSD's mission and values.

The interview process for a Data Scientist role at MSD is structured to ensure a thorough evaluation of both technical skills and cultural fit. It typically consists of multiple rounds, each designed to assess different competencies and experiences relevant to the position.

1. Initial Screening

The process begins with an initial screening call, usually conducted by a recruiter or HR representative. This conversation lasts about 30 minutes and focuses on your background, motivations for applying, and a brief overview of the company and the role. The recruiter will also gauge your alignment with MSD's values and culture, which is a critical aspect of their hiring process.

2. Technical Interview

Following the initial screening, candidates typically participate in a technical interview. This round may involve one or more interviewers, including hiring managers or senior data scientists. The technical interview assesses your knowledge of data science concepts, statistical methods, and relevant technologies. Expect questions that require you to discuss your previous projects in detail, including the design and implementation of data pipelines, as well as problem-solving scenarios related to data analysis and modeling.

3. Behavioral and Situational Assessment

In addition to technical skills, MSD places a strong emphasis on behavioral and situational assessments. Candidates may be asked to describe past work experiences, particularly those that demonstrate adaptability, teamwork, and problem-solving abilities. This round often includes situational questions that explore how you handle challenges and collaborate with diverse teams.

4. Final Interview

The final interview may involve a panel of interviewers, including team members and possibly higher management. This round often includes a case study or presentation where you will need to articulate your thought process and solutions to a given problem. It is also an opportunity for you to ask questions about the team dynamics and ongoing projects at MSD.

Throughout the interview process, candidates should be prepared for a conversational style of questioning, which allows for a more natural dialogue about experiences and skills.

As you prepare for your interviews, consider the types of questions that may arise in each of these rounds.

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

Embrace the Conversational Atmosphere

The interview process at MSD is known for its positive and open dialogue. Approach your interviews as conversations rather than interrogations. This mindset will help you feel more relaxed and allow your personality to shine through. Be prepared to discuss your experiences and projects in a narrative format, as this aligns with the interviewers' preference for understanding your journey and thought processes.

Prepare for Behavioral and Situational Questions

Expect a significant focus on behavioral and situational questions that assess your adaptability and interpersonal skills. Reflect on your past experiences and be ready to share specific examples that demonstrate your problem-solving abilities, teamwork, and how you handle challenges. Use the STAR (Situation, Task, Action, Result) method to structure your responses effectively.

Showcase Your Technical Expertise

While the interview process includes a conversational element, be prepared for technical assessments as well. Brush up on relevant technologies and methodologies that are pertinent to the role of a Data Scientist. Be ready to discuss your previous projects in detail, including the technologies you used, the challenges you faced, and how you overcame them. This will not only demonstrate your technical skills but also your ability to communicate complex ideas clearly.

Understand the Company Culture

MSD values well-rounded individuals who align with their company culture. Familiarize yourself with their core values and mission. During the interview, express how your personal values and work ethic resonate with those of the company. This alignment can significantly enhance your candidacy.

Be Ready for a Panel Interview

The interview process may involve multiple interviewers, including managers and team members. Prepare to engage with different personalities and perspectives. Practice articulating your thoughts clearly and confidently, as you may be asked to present your ideas or solutions to a group. This will also help you gauge the dynamics of the team you could potentially join.

Ask Insightful Questions

At the end of your interview, you will likely have the opportunity to ask questions. Use this time wisely to inquire about the team dynamics, ongoing projects, and the company’s future direction. Asking thoughtful questions not only shows your interest in the role but also helps you assess if MSD is the right fit for you.

Follow Up Professionally

After your interview, consider sending a thank-you email to express your appreciation for the opportunity to interview. This is a chance to reiterate your enthusiasm for the role and the company. A well-crafted follow-up can leave a lasting impression and demonstrate your professionalism.

By following these tips, you can approach your interview with confidence and clarity, positioning yourself as a strong candidate for the Data Scientist role at MSD. Good luck!

In this section, we’ll review the various interview questions that might be asked during a Data Scientist interview at MSD. The interview process will likely assess a combination of technical skills, problem-solving abilities, and cultural fit within the organization. Candidates should be prepared to discuss their previous projects, technical expertise, and how they approach data-driven challenges.

Technical Skills

1. Can you walk us through a specific project where you had to design and implement a data pipeline from start to finish? What challenges did you encounter, and how did you overcome them?

This question aims to evaluate your hands-on experience with data pipelines and your problem-solving skills in real-world scenarios.

How to Answer

Discuss a project where you played a key role in designing and implementing a data pipeline. Highlight the challenges you faced and the strategies you employed to overcome them.

Example

“In my last role, I designed a data pipeline for processing customer feedback. The main challenge was ensuring data quality, as we were pulling from multiple sources. I implemented validation checks at each stage of the pipeline, which significantly improved the accuracy of our insights.”

2. What technologies would you use for a multi-cloud solution?

This question assesses your knowledge of cloud technologies and your ability to choose the right tools for specific scenarios.

How to Answer

Mention specific cloud platforms and technologies you are familiar with, and explain why you would choose them for a multi-cloud solution.

Example

“I would consider using AWS for its robust data storage options, Azure for its machine learning capabilities, and Google Cloud for its data analytics tools. This combination allows for flexibility and optimization based on the specific needs of the project.”

3. What is Apache Spark, and why would you use it?

This question tests your understanding of big data technologies and their applications.

How to Answer

Explain what Apache Spark is and its advantages in processing large datasets.

Example

“Apache Spark is an open-source distributed computing system that provides an interface for programming entire clusters with implicit data parallelism and fault tolerance. I would use it for its speed and ability to handle large-scale data processing tasks efficiently.”

4. Describe a case study from your previous job.

This question allows you to showcase your analytical skills and how you apply them in a business context.

How to Answer

Select a case study that highlights your analytical approach and the impact of your work.

Example

“I worked on a case study analyzing customer churn. By applying machine learning models, we identified key factors contributing to churn and implemented targeted retention strategies, which reduced churn by 15% over six months.”

5. How do you approach optimizing data storage and retrieval processes?

This question evaluates your problem-solving skills and technical knowledge in data management.

How to Answer

Discuss your methodology for assessing and improving data storage and retrieval.

Example

“I start by analyzing the current data architecture to identify bottlenecks. Then, I would consider implementing indexing strategies, partitioning data, and utilizing caching mechanisms to enhance performance.”

Behavioral Questions

1. Describe a situation where you had to collaborate with a diverse team to achieve a common goal. How did you navigate different perspectives, and what was the outcome?

This question assesses your teamwork and interpersonal skills.

How to Answer

Share an experience where you worked with a diverse group, focusing on how you facilitated collaboration and resolved conflicts.

Example

“I was part of a project team with members from different departments. I organized regular check-ins to ensure everyone’s voice was heard, which helped us align our goals and ultimately led to a successful product launch.”

2. What was the biggest challenge you faced at work, and how did you overcome it?

This question evaluates your resilience and problem-solving abilities.

How to Answer

Choose a significant challenge and explain the steps you took to address it.

Example

“I faced a challenge when a key project was behind schedule due to unforeseen technical issues. I organized a brainstorming session with the team to identify solutions, which led us to reallocate resources and ultimately meet our deadline.”

3. How do you handle tight deadlines and pressure?

This question assesses your time management and stress management skills.

How to Answer

Discuss your strategies for managing time and maintaining quality under pressure.

Example

“I prioritize tasks based on urgency and impact. During a recent project with a tight deadline, I broke down the work into manageable chunks and communicated regularly with my team to ensure we stayed on track.”

4. Why do you want to work with us?

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

How to Answer

Express your interest in the company and how it aligns with your career goals.

Example

“I admire MSD’s commitment to innovation in healthcare. I believe my skills in data science can contribute to meaningful projects that improve patient outcomes, which aligns with my passion for using data to drive positive change.”

5. Can you describe a time when you had to give constructive feedback to a colleague?

This question evaluates your communication skills and ability to foster a positive work environment.

How to Answer

Share an experience where you provided feedback and the outcome of that interaction.

Example

“I once had to give feedback to a colleague about their presentation style. I approached the conversation with empathy, highlighting their strengths first and then suggesting areas for improvement. They appreciated the feedback and made significant changes for their next presentation.”