Interview Guides

Novartis

Research Scientist

What is a Research Scientist at Novartis?

The role of a Research Scientist at Novartis is pivotal in driving innovation and scientific discovery within the pharmaceutical industry. As a Research Scientist, you will engage in cutting-edge research aimed at identifying and optimizing drug candidates, contributing to the development of therapies that improve patient outcomes. This role requires a strong foundation in scientific principles, creativity in experimental design, and the ability to collaborate across various disciplines.

Research Scientists at Novartis work on diverse projects ranging from lead identification to preclinical development. You will have the opportunity to contribute to significant advancements in healthcare, tackling complex diseases through innovative research methodologies. This role is not only critical for the success of the company's pipeline but also offers a rewarding experience as you help shape the future of medicine.

As part of a global team, your influence will extend beyond the laboratory, impacting strategic decisions and the overall direction of research initiatives. Expect to be challenged and inspired as you work alongside top scientists and utilize advanced technologies to push the boundaries of what is possible in drug discovery.

Common Interview Questions

In preparing for your interviews with Novartis, you should expect a range of questions that assess both your technical capabilities and your fit within the company culture. The following categories reflect common themes seen in interviews for the Research Scientist role, drawn from 1point3acres.com and other sources. Keep in mind that while these questions are representative, they may vary by team.

Technical / Domain Questions

These questions evaluate your scientific knowledge and expertise relevant to the role of a Research Scientist.

Describe a successful research project you led. What were the key factors that contributed to its success?
What methods do you use for lead optimization, and why are they effective?
Can you explain a complex scientific concept to a non-scientific audience?
Discuss a time when you had to troubleshoot an experiment. What was the issue, and how did you resolve it?
What are the latest trends in drug discovery that you find most exciting?

Behavioral / Leadership

Expect questions focused on your past experiences and how they align with Novartis values.

Tell me about a time you faced a significant challenge in your work. How did you handle it?
Describe a situation where you had to work collaboratively with a difficult team member. What was the outcome?
How do you prioritize your tasks when working on multiple projects?
Give an example of how you have demonstrated leadership in your previous roles.
How do you handle feedback and criticism of your work?

Problem-solving / Case Studies

These questions will assess your analytical skills and your approach to scientific problems.

You are given a dataset with unexpected results. What steps would you take to analyze and interpret this data?
How would you design an experiment to test a new hypothesis?
If you were tasked with developing a drug for a disease with limited research, what approach would you take?
Discuss a case study where you had to pivot your research direction. What prompted the change?

Cultural Fit / Values

These questions gauge your alignment with Novartis’ mission and workplace culture.

What draws you to Novartis specifically?
How do you align your personal values with a company’s mission?
Describe a time when you contributed to a positive team culture.
What does diversity and inclusion mean to you in a workplace setting?

See every interview question for this role

Practice questions from our question bank

Curated questions for Novartis from real interviews. Click any question to practice and review the answer.

Medium

NLP

Compare Positional Encodings in Transformers

Implement and compare sinusoidal vs learned positional encodings in a Transformer for legal clause classification where word order changes meaning.

Tokenization

Language Models

Deep Learning

Medium

Statistics & Probability

Root-Cause a Failing QC Assay

Use normal/t-tests and a lot-comparison Welch test to decide if a QC assay failure indicates a true mean shift or a bad reagent lot.

Hypothesis Testing

Statistical Significance

Experimentation

Hard

Model Evaluation

Evaluate MIMO Channel Estimation Errors

Assess how rising channel estimation error in a 4x4 MIMO system drives BER, outage, and throughput degradation, and recommend fixes.

Accuracy

Calibration

Medium

Machine Learning

Predict Turbine Failures from Sensor Data

Build a gradient-boosted classifier to predict turbine failures 7 days ahead from sensor, alarm, and maintenance history data.

Supervised Learning

Cross-Validation

Feature Engineering

Easy

NLP

Classify RL-LLM Research Interests

Build a transformer-based multi-label classifier to categorize candidate statements about RL and LLM research interests into recruiting themes.

Tokenization

Language Models

Deep Learning

Medium

Machine Learning

Harden Vision Models Against Adversarial Attacks

Train a CNN for traffic-sign classification, measure adversarial robustness with FGSM, and improve deployed-model resilience with adversarial training.

Regularization

Neural Networks

Deep Learning

Medium

Machine Learning

Rank Human Preferences for RLHF

Train a pairwise preference model for RLHF that predicts which LLM response humans prefer and produces deployable reward scores.

Supervised Learning

Regularization

Deep Learning

Hard

Machine Learning

Conditioned Reverse Diffusion Process for User Prompts

Develop a reverse diffusion model conditioned on user editing prompts for text generation tasks.

Neural Networks

Gradient Descent

Deep Learning

Easy

Coding

Explain Solution Time Complexity

Explain how to analyze a coding solution's time complexity by counting operations, loops, and data structure costs.

Arrays

Sorting

Searching

Hard

NLP

Explain Transformer Architecture and Attention Mechanisms

Discuss the architecture of Transformers, focusing on self-attention and its impact on NLP tasks.

Neural Networks

Language Models

Deep Learning

Medium

Machine Learning

Build a Multimodal LLM for Real-Time Video Editing

Develop a multimodal large language model to enhance user experience in real-time video editing applications.

Supervised Learning

Deep Learning

Feature Engineering

Easy

Statistics & Probability

Explain P-Value in Marketing Test

Use a two-proportion z-test to assess a banner A/B test, then explain the resulting p-value clearly to a non-technical stakeholder.

Hypothesis Testing

Confidence Intervals

P-Values

Easy

Statistics & Probability

P-Value and Power for Button Redesign

Use a two-proportion z-test and power analysis to explain whether a 1-point signup lift from a button redesign is statistically credible.

Hypothesis Testing

P-Values

Power Analysis

Easy

Model Evaluation

Choose RMSE vs MAE

Compare two rent prediction models and decide whether MAE or RMSE is the better selection metric given costly large errors.

Regression

RMSE

MAE

Easy

Model Evaluation

Choose RMSE or MAE

Explain RMSE vs MAE using two rent prediction models and recommend which metric and model better fit a business sensitive to large errors.

Regression

RMSE

MAE

Easy

Statistics & Probability

Confidence Interval for Email CTR Test

Construct and interpret a 95% confidence interval for the CTR lift in an email A/B test to communicate uncertainty in the experiment result.

Confidence Intervals

Statistical Significance

Experimentation

Easy

Statistics & Probability

Explaining P-Value and Power

Compute a two-proportion z-test and explain p-value and statistical power for an onboarding experiment with an inconclusive result.

Hypothesis Testing

P-Values

Power Analysis

Hard

Machine Learning

Analyze Self-Attention for Feed Ranking

Explain and implement scaled dot-product self-attention for Facebook Feed text ranking, including tensor shapes, training setup, and complexity analysis.

Neural Networks

Gradient Descent

Deep Learning

Hard

Coding

Serialize and Deserialize Binary Tree

Serialize a binary tree to a string and reconstruct it exactly using preorder traversal with null markers.

Trees

Recursion

Queue

Easy

Execution

Pivot FAIR Research for Reels Launch

Pivot a FAIR ranking project from Facebook Feed to Instagram Reels in 10 weeks under latency, fairness, and integration constraints.

Roadmapping

Trade-offs

Risk Assessment

Sign up to see all questions

Create a free account to access every interview question for this role.

Getting Ready for Your Interviews

Preparation for your interviews at Novartis should be comprehensive and focused. You will be evaluated on several key criteria that reflect the expectations for the Research Scientist role.

Role-related knowledge – This criterion assesses your scientific expertise, including knowledge of current research methodologies and technologies relevant to drug discovery. Be prepared to demonstrate your understanding of specific techniques and how they apply to the projects at Novartis.

Problem-solving ability – Interviewers will evaluate how you approach challenges and structure your solutions. Highlight instances where your analytical skills led to successful outcomes in your research.

Leadership – As a Research Scientist, you will need to influence and collaborate effectively. Showcase your ability to lead projects, mentor others, and communicate clearly within a team.

Culture fit / values – Novartis places a strong emphasis on its core values. Be ready to discuss how your personal values align with the company's mission and how you contribute to a collaborative work environment.

Interview Process Overview

The interview process for the Research Scientist position at Novartis is typically well-structured and engaging, consisting of multiple stages designed to assess both your technical abilities and interpersonal fit. Candidates can expect an initial screening by HR, followed by interviews with hiring managers and potential team members. The emphasis is often on both your scientific expertise and how well you work within a team dynamic.

Throughout the process, be prepared for a mix of informal discussions and formal presentations. You may be asked to present your previous research, engage in case studies, and participate in behavioral interviews. It's important to approach each stage with confidence and a clear understanding of Novartis’ research goals and values.

The visual timeline of the interview process highlights the various stages, including initial screenings, technical interviews, and final presentations. Use this timeline to plan your preparation and manage your energy throughout the interview stages. Familiarize yourself with the typical flow to ensure you are well-prepared for each component.

Deep Dive into Evaluation Areas

Understanding the specific areas in which you will be evaluated is crucial for your preparation. Here are the major evaluation areas for the Research Scientist role at Novartis:

Technical Expertise

This area assesses your deep scientific knowledge and competence in research methodologies. Strong performance involves demonstrating a solid understanding of current trends and techniques in drug discovery.

Experimental Design – How to plan and execute experiments effectively.
Data Analysis – Proficiency in interpreting and presenting research data.
Research Trends – Awareness of the latest developments in pharmaceutical research.

Example questions or scenarios:

"Design a study to evaluate the efficacy of a new drug candidate."
"How would you analyze unexpected results from your experiments?"

Problem-solving Skills

Your ability to tackle complex scientific challenges will be scrutinized. Interviewers will look for systematic approaches to problem-solving and critical thinking.

Analytical Thinking – How to break down problems into manageable components.
Creativity in Solutions – Innovative approaches to overcoming research obstacles.

Example questions or scenarios:

"What would be your approach if your initial hypothesis was proven wrong during experimentation?"

Collaboration and Communication

Collaboration is key in a research environment. You will need to communicate effectively with interdisciplinary teams.

Interpersonal Skills – Ability to work well with others and influence team dynamics.
Presentation Skills – Capacity to convey complex scientific concepts clearly.

Example questions or scenarios:

"How would you explain your research to stakeholders who are not scientists?"

Key Responsibilities

As a Research Scientist at Novartis, your day-to-day responsibilities will encompass a variety of tasks central to the drug discovery process. You will be involved in designing experiments, analyzing data, and collaborating with cross-functional teams to advance research initiatives.

Your primary responsibilities will include:

Conducting experiments and analyzing results to identify promising drug candidates.
Collaborating with chemists, biologists, and other scientists to refine research objectives.
Presenting findings in team meetings and contributing to project strategy discussions.
Documenting research processes and outcomes in compliance with regulatory standards.

This role demands not only technical skills but also the ability to engage with colleagues, share insights, and contribute to a positive research culture.

Role Requirements & Qualifications

To be considered a strong candidate for the Research Scientist position at Novartis, you should meet the following qualifications:

Technical skills – Proficiency in relevant laboratory techniques and data analysis tools.
Experience level – Typically, candidates should have a PhD or equivalent experience in a related field, along with several years of research experience.
Soft skills – Strong communication, teamwork, and leadership capabilities are essential for success in this role.
Must-have skills – Expertise in drug discovery processes and familiarity with regulatory requirements.
Nice-to-have skills – Experience in cross-disciplinary collaboration or advanced statistical analysis.

Candidates who can demonstrate a blend of technical expertise and strong interpersonal skills will be well-positioned for success.

Frequently Asked Questions

Q: How difficult is the interview process? The interview process is generally considered rigorous, with a mix of technical and behavioral questions. Candidates should prepare for both types of inquiries, dedicating sufficient time to study.

Q: What differentiates successful candidates? Successful candidates typically demonstrate strong technical knowledge, problem-solving skills, and the ability to collaborate effectively within teams. Clear communication and alignment with Novartis’ values are also crucial.

Q: What is the timeline from application to offer? The timeline can vary, but candidates often experience a multi-week process from initial screening to final interviews. Expect to be patient, as thorough evaluations are standard.

Q: How does Novartis foster a collaborative environment? Novartis promotes a culture of teamwork and open communication. Research Scientists are encouraged to share ideas and work together across disciplines to drive innovation.

Q: Are there remote work options? While many positions allow for flexibility, the specifics depend on the team and project needs. Candidates should clarify expectations during the interview process.

Other General Tips

Understand the Mission: Familiarize yourself with Novartis’ mission and recent developments in their research focus. This knowledge will help you demonstrate your alignment with their goals.
Practice Your Presentation: Be prepared to present your past research clearly and confidently. This is often a key component of the interview process.
Engage with Interviewers: Show genuine interest in the work being done at Novartis. Engage with your interviewers and ask insightful questions about their projects.
Demonstrate Adaptability: Be prepared to discuss how you have adapted your research strategies in response to changing circumstances or new information.

Note

Be aware that many candidates report a competitive interview process. Prepare thoroughly and be ready to showcase your unique qualifications.

Summary & Next Steps

The Research Scientist role at Novartis offers a unique opportunity to contribute to meaningful advancements in healthcare. Your preparation should center on understanding the evaluation themes, familiarizing yourself with the types of questions you may encounter, and aligning your experiences with the company's values.

Focus on refining your technical knowledge, enhancing your problem-solving skills, and showcasing your collaborative spirit. Remember that thorough preparation can significantly enhance your chances of success. For more insights and resources, explore additional interview insights on Dataford.

You have the potential to make a significant impact at Novartis, and with dedicated preparation, you can position yourself as a strong candidate for this exciting opportunity.

The salary range for the Research Scientist position at Novartis is between $81,200 and$ 150,800 USD. Understanding this range will help you gauge your expectations and negotiate effectively if you receive an offer.

Sign up to read the full guide

Create a free account to unlock the complete interview guide with all sections.

Novartis

Research Scientist

Build my plan

What is a Research Scientist at Novartis?

Common Interview Questions

Technical / Domain Questions

These questions evaluate your scientific knowledge and expertise relevant to the role of a Research Scientist.

Describe a successful research project you led. What were the key factors that contributed to its success?
What methods do you use for lead optimization, and why are they effective?
Can you explain a complex scientific concept to a non-scientific audience?
Discuss a time when you had to troubleshoot an experiment. What was the issue, and how did you resolve it?
What are the latest trends in drug discovery that you find most exciting?

Behavioral / Leadership

Expect questions focused on your past experiences and how they align with Novartis values.

Tell me about a time you faced a significant challenge in your work. How did you handle it?
Describe a situation where you had to work collaboratively with a difficult team member. What was the outcome?
How do you prioritize your tasks when working on multiple projects?
Give an example of how you have demonstrated leadership in your previous roles.
How do you handle feedback and criticism of your work?

Problem-solving / Case Studies

These questions will assess your analytical skills and your approach to scientific problems.

You are given a dataset with unexpected results. What steps would you take to analyze and interpret this data?
How would you design an experiment to test a new hypothesis?
If you were tasked with developing a drug for a disease with limited research, what approach would you take?
Discuss a case study where you had to pivot your research direction. What prompted the change?

Cultural Fit / Values

These questions gauge your alignment with Novartis’ mission and workplace culture.

What draws you to Novartis specifically?
How do you align your personal values with a company’s mission?
Describe a time when you contributed to a positive team culture.
What does diversity and inclusion mean to you in a workplace setting?

See every interview question for this role

Practice questions from our question bank

Curated questions for Novartis from real interviews. Click any question to practice and review the answer.

Medium

NLP

Compare Positional Encodings in Transformers

Implement and compare sinusoidal vs learned positional encodings in a Transformer for legal clause classification where word order changes meaning.

Tokenization

Language Models

Deep Learning

Medium

Statistics & Probability

Root-Cause a Failing QC Assay

Use normal/t-tests and a lot-comparison Welch test to decide if a QC assay failure indicates a true mean shift or a bad reagent lot.

Hypothesis Testing

Statistical Significance

Experimentation

Hard

Model Evaluation

Evaluate MIMO Channel Estimation Errors

Assess how rising channel estimation error in a 4x4 MIMO system drives BER, outage, and throughput degradation, and recommend fixes.

Accuracy

Calibration

Medium

Machine Learning

Predict Turbine Failures from Sensor Data

Build a gradient-boosted classifier to predict turbine failures 7 days ahead from sensor, alarm, and maintenance history data.

Supervised Learning

Cross-Validation

Feature Engineering

Easy

NLP

Classify RL-LLM Research Interests

Build a transformer-based multi-label classifier to categorize candidate statements about RL and LLM research interests into recruiting themes.

Tokenization

Language Models

Deep Learning

Medium

Machine Learning

Harden Vision Models Against Adversarial Attacks

Train a CNN for traffic-sign classification, measure adversarial robustness with FGSM, and improve deployed-model resilience with adversarial training.

Regularization

Neural Networks

Deep Learning

Medium

Machine Learning

Rank Human Preferences for RLHF

Train a pairwise preference model for RLHF that predicts which LLM response humans prefer and produces deployable reward scores.

Supervised Learning

Regularization

Deep Learning

Hard

Machine Learning

Conditioned Reverse Diffusion Process for User Prompts

Develop a reverse diffusion model conditioned on user editing prompts for text generation tasks.

Neural Networks

Gradient Descent

Deep Learning

Easy

Coding

Explain Solution Time Complexity

Explain how to analyze a coding solution's time complexity by counting operations, loops, and data structure costs.

Arrays

Sorting

Searching

Hard

NLP

Explain Transformer Architecture and Attention Mechanisms

Discuss the architecture of Transformers, focusing on self-attention and its impact on NLP tasks.

Neural Networks

Language Models

Deep Learning

Medium

Machine Learning

Build a Multimodal LLM for Real-Time Video Editing

Develop a multimodal large language model to enhance user experience in real-time video editing applications.

Supervised Learning

Deep Learning

Feature Engineering

Easy

Statistics & Probability

Explain P-Value in Marketing Test

Use a two-proportion z-test to assess a banner A/B test, then explain the resulting p-value clearly to a non-technical stakeholder.

Hypothesis Testing

Confidence Intervals

P-Values

Easy

Statistics & Probability

P-Value and Power for Button Redesign

Use a two-proportion z-test and power analysis to explain whether a 1-point signup lift from a button redesign is statistically credible.

Hypothesis Testing

P-Values

Power Analysis

Easy

Model Evaluation

Choose RMSE vs MAE

Compare two rent prediction models and decide whether MAE or RMSE is the better selection metric given costly large errors.

Regression

RMSE

MAE

Easy

Model Evaluation

Choose RMSE or MAE

Explain RMSE vs MAE using two rent prediction models and recommend which metric and model better fit a business sensitive to large errors.

Regression

RMSE

MAE

Easy

Statistics & Probability

Confidence Interval for Email CTR Test

Construct and interpret a 95% confidence interval for the CTR lift in an email A/B test to communicate uncertainty in the experiment result.

Confidence Intervals

Statistical Significance

Experimentation

Easy

Statistics & Probability

Explaining P-Value and Power

Compute a two-proportion z-test and explain p-value and statistical power for an onboarding experiment with an inconclusive result.

Hypothesis Testing

P-Values

Power Analysis

Hard

Machine Learning

Analyze Self-Attention for Feed Ranking

Explain and implement scaled dot-product self-attention for Facebook Feed text ranking, including tensor shapes, training setup, and complexity analysis.

Neural Networks

Gradient Descent

Deep Learning

Hard

Coding

Serialize and Deserialize Binary Tree

Serialize a binary tree to a string and reconstruct it exactly using preorder traversal with null markers.

Trees

Recursion

Queue

Easy

Execution

Pivot FAIR Research for Reels Launch

Pivot a FAIR ranking project from Facebook Feed to Instagram Reels in 10 weeks under latency, fairness, and integration constraints.

Roadmapping

Trade-offs

Risk Assessment

Sign up to see all questions

Create a free account to access every interview question for this role.

Getting Ready for Your Interviews

Preparation for your interviews at Novartis should be comprehensive and focused. You will be evaluated on several key criteria that reflect the expectations for the Research Scientist role.

Leadership – As a Research Scientist, you will need to influence and collaborate effectively. Showcase your ability to lead projects, mentor others, and communicate clearly within a team.

Interview Process Overview

Deep Dive into Evaluation Areas

Understanding the specific areas in which you will be evaluated is crucial for your preparation. Here are the major evaluation areas for the Research Scientist role at Novartis:

Technical Expertise

Experimental Design – How to plan and execute experiments effectively.
Data Analysis – Proficiency in interpreting and presenting research data.
Research Trends – Awareness of the latest developments in pharmaceutical research.

Example questions or scenarios:

"Design a study to evaluate the efficacy of a new drug candidate."
"How would you analyze unexpected results from your experiments?"

Problem-solving Skills

Your ability to tackle complex scientific challenges will be scrutinized. Interviewers will look for systematic approaches to problem-solving and critical thinking.

Analytical Thinking – How to break down problems into manageable components.
Creativity in Solutions – Innovative approaches to overcoming research obstacles.

Example questions or scenarios:

"What would be your approach if your initial hypothesis was proven wrong during experimentation?"

Collaboration and Communication

Collaboration is key in a research environment. You will need to communicate effectively with interdisciplinary teams.

Interpersonal Skills – Ability to work well with others and influence team dynamics.
Presentation Skills – Capacity to convey complex scientific concepts clearly.

Example questions or scenarios:

"How would you explain your research to stakeholders who are not scientists?"

Key Responsibilities

Your primary responsibilities will include:

Conducting experiments and analyzing results to identify promising drug candidates.
Collaborating with chemists, biologists, and other scientists to refine research objectives.
Presenting findings in team meetings and contributing to project strategy discussions.
Documenting research processes and outcomes in compliance with regulatory standards.

This role demands not only technical skills but also the ability to engage with colleagues, share insights, and contribute to a positive research culture.

Role Requirements & Qualifications

To be considered a strong candidate for the Research Scientist position at Novartis, you should meet the following qualifications:

Technical skills – Proficiency in relevant laboratory techniques and data analysis tools.
Experience level – Typically, candidates should have a PhD or equivalent experience in a related field, along with several years of research experience.
Soft skills – Strong communication, teamwork, and leadership capabilities are essential for success in this role.
Must-have skills – Expertise in drug discovery processes and familiarity with regulatory requirements.
Nice-to-have skills – Experience in cross-disciplinary collaboration or advanced statistical analysis.

Candidates who can demonstrate a blend of technical expertise and strong interpersonal skills will be well-positioned for success.

Frequently Asked Questions

Other General Tips

Understand the Mission: Familiarize yourself with Novartis’ mission and recent developments in their research focus. This knowledge will help you demonstrate your alignment with their goals.
Practice Your Presentation: Be prepared to present your past research clearly and confidently. This is often a key component of the interview process.
Engage with Interviewers: Show genuine interest in the work being done at Novartis. Engage with your interviewers and ask insightful questions about their projects.
Demonstrate Adaptability: Be prepared to discuss how you have adapted your research strategies in response to changing circumstances or new information.

Note

Be aware that many candidates report a competitive interview process. Prepare thoroughly and be ready to showcase your unique qualifications.

Summary & Next Steps

You have the potential to make a significant impact at Novartis, and with dedicated preparation, you can position yourself as a strong candidate for this exciting opportunity.

Sign up to read the full guide

Create a free account to unlock the complete interview guide with all sections.