Eli Lilly And Company Data Scientist Interview Questions + Guide in 2025

Eli Lilly and Company is a global healthcare leader dedicated to discovering and delivering life-changing medicines to those in need while fostering a culture of care and innovation.

As a Data Scientist at Eli Lilly, you will play a pivotal role in the Advanced Analytics and Data Sciences (AADS) team, leveraging data to solve complex business and scientific problems that ultimately improve patient outcomes. Your key responsibilities will include partnering with business and research teams to identify and execute visual analytics efforts, maintaining a broad understanding of the pharmaceutical landscape, and designing and deploying enterprise-level analytics solutions. You will be expected to stay current with statistical methodologies and advanced analytics techniques, collaborate with cross-functional teams, and communicate insights effectively using data storytelling methods.

Ideal candidates will possess a PhD in a quantitative field such as Statistics, Biostatistics, or Computer Science, or a Master’s degree with substantial industry experience. Profound skills in programming languages like Python and R, as well as experience with machine learning and statistical modeling, are essential. You should also demonstrate strong analytical, problem-solving, and communication skills, along with the ability to influence stakeholders and foster a collaborative environment.

This guide will help you prepare for your interview by providing insights into the responsibilities and expectations of the Data Scientist role at Eli Lilly, ensuring you can effectively articulate your qualifications and how they align with the company’s mission and values.

The interview process for a Data Scientist role at Eli Lilly is structured and thorough, reflecting the company’s commitment to finding the right candidates who align with their mission of improving lives through innovative healthcare solutions. The process typically consists of several key stages:

1. Initial Screening

The first step in the interview process is an initial screening, which usually takes place via a phone call with a recruiter or hiring manager. This conversation lasts about 30 minutes and focuses on your background, experiences, and motivations for wanting to work at Eli Lilly. Expect to discuss your resume in detail, including your technical skills and any relevant projects. The recruiter will also assess your fit with the company culture and values.

2. Technical Assessment

Following the initial screening, candidates may be invited to complete a technical assessment. This could involve a coding challenge or a take-home assignment that tests your proficiency in programming languages such as Python or R, as well as your understanding of data science concepts and methodologies. The assessment is designed to evaluate your analytical skills and ability to solve complex problems using data.

3. Technical Interview

If you successfully pass the technical assessment, the next step is a technical interview. This interview typically involves one or more data scientists or technical leads who will ask you to solve problems in real-time. You may be presented with case studies or hypothetical scenarios relevant to the pharmaceutical industry, where you will need to demonstrate your analytical thinking, statistical knowledge, and familiarity with machine learning algorithms. Be prepared to discuss your previous work experiences and how they relate to the role.

4. Behavioral Interview

In addition to technical skills, Eli Lilly places a strong emphasis on cultural fit and interpersonal skills. The behavioral interview will focus on your past experiences and how you handle various situations in a team environment. Expect to answer questions using the STAR (Situation, Task, Action, Result) method to illustrate your problem-solving abilities and teamwork experiences. Interviewers will be looking for evidence of your communication skills, adaptability, and ability to influence others.

5. Final Interview

The final stage of the interview process may involve a panel interview or a series of one-on-one interviews with senior leaders or cross-functional team members. This is an opportunity for you to showcase your understanding of the pharmaceutical industry and how data science can drive business decisions. You may also be asked to present a project or case study that highlights your analytical capabilities and your approach to solving business problems.

Throughout the interview process, candidates are encouraged to ask questions about the company, team dynamics, and the specific projects they would be working on. This not only demonstrates your interest in the role but also helps you assess if Eli Lilly is the right fit for you.

As you prepare for your interview, consider the types of questions that may be asked in each stage of the process.

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

Embrace the Company Culture

Eli Lilly emphasizes a culture of caring, collaboration, and community involvement. Familiarize yourself with their mission to improve lives through innovative healthcare solutions. During the interview, express your alignment with these values and share examples of how you have contributed to team success or community initiatives in your previous roles. This will demonstrate that you are not only a skilled data scientist but also a good cultural fit for the organization.

Prepare for Behavioral Questions

Expect a significant focus on behavioral questions, particularly those that utilize the STAR (Situation, Task, Action, Result) method. Reflect on your past experiences and prepare to discuss specific instances where you faced challenges, collaborated with teams, or influenced decisions. Given the friendly nature of the interviewers, approach these questions with confidence and authenticity, showcasing your problem-solving skills and ability to work in diverse teams.

Highlight Technical Proficiency

As a data scientist, you will be expected to demonstrate your technical skills, particularly in programming languages like Python and R, as well as your understanding of machine learning algorithms and data visualization techniques. Be prepared to discuss your experience with specific projects, the methodologies you employed, and the impact of your work. If you have a portfolio of work, ensure it is polished and ready to share, as this can significantly enhance your candidacy.

Engage with Your Interviewers

The interview process at Eli Lilly often includes informal interactions, such as lunch with employees. Use these opportunities to engage with your interviewers on a personal level. Ask insightful questions about their experiences at the company, the projects they are working on, and how they see the role of data science evolving within the organization. This not only shows your interest in the company but also helps you gauge if it’s the right fit for you.

Be Ready for Technical Assessments

While some candidates reported that technical assessments were straightforward, others faced more challenging questions related to data structures and algorithms. Brush up on your data science fundamentals, including statistical methods, machine learning concepts, and data manipulation techniques. Practice coding problems on platforms like LeetCode or HackerRank to ensure you are comfortable with the technical aspects of the role.

Communicate Clearly and Effectively

Given the emphasis on collaboration and communication at Eli Lilly, practice articulating your thoughts clearly and concisely. Be prepared to explain complex technical concepts in a way that is accessible to non-technical stakeholders. This skill is crucial for a data scientist who needs to influence decision-making based on data insights.

Stay Patient and Positive

The interview process can be lengthy, and candidates have noted varying timelines for feedback. Maintain a positive attitude throughout the process, and don’t hesitate to follow up if you haven’t heard back within the expected timeframe. This demonstrates your continued interest in the position and your proactive nature.

By following these tailored tips, you can present yourself as a well-rounded candidate who not only possesses the necessary technical skills but also embodies the values and culture of Eli Lilly. Good luck!

In this section, we’ll review the various interview questions that might be asked during a Data Scientist interview at Eli Lilly and Company. The interview process will likely focus on a combination of technical skills, problem-solving abilities, and behavioral competencies, reflecting the company’s commitment to innovation and collaboration in the healthcare sector. Candidates should be prepared to discuss their experiences, technical knowledge, and how they can contribute to the company’s mission of improving patient outcomes.

Technical Skills

1. Describe a machine learning project you have worked on. What were the challenges, and how did you overcome them?

This question assesses your practical experience with machine learning and your problem-solving skills.

How to Answer

Discuss a specific project, focusing on the challenges you faced and the strategies you employed to address them. Highlight your technical skills and how they contributed to the project’s success.

Example

“In my last project, I developed a predictive model for patient readmission rates. One major challenge was dealing with missing data. I implemented imputation techniques and feature engineering to enhance the model’s accuracy, which ultimately improved our predictions by 15%.”

2. How do you ensure the quality and integrity of your data?

This question evaluates your understanding of data management practices.

How to Answer

Explain the methods you use to validate and clean data, emphasizing the importance of data quality in analytics.

Example

“I use a combination of automated scripts and manual checks to identify anomalies in the data. I also implement data validation rules at the point of entry to minimize errors and ensure that the data used for analysis is accurate and reliable.”

3. Can you explain the difference between supervised and unsupervised learning?

This question tests your foundational knowledge of machine learning concepts.

How to Answer

Provide clear definitions and examples of both types of learning, demonstrating your understanding of their applications.

Example

“Supervised learning involves training a model on labeled data, where the outcome is known, such as predicting house prices based on features like size and location. In contrast, unsupervised learning deals with unlabeled data, aiming to find hidden patterns, like clustering customers based on purchasing behavior.”

4. What programming languages and tools are you proficient in for data analysis?

This question assesses your technical skills and familiarity with industry-standard tools.

How to Answer

List the programming languages and tools you are comfortable with, providing examples of how you have used them in your work.

Example

“I am proficient in Python and R for data analysis, using libraries like Pandas and ggplot2 for data manipulation and visualization. I also have experience with SQL for database querying and Tableau for creating interactive dashboards.”

5. Describe a time when you had to communicate complex data findings to a non-technical audience.

This question evaluates your communication skills and ability to convey technical information effectively.

How to Answer

Share a specific instance where you simplified complex data insights for a non-technical audience, focusing on your approach and the outcome.

Example

“I presented the results of a market analysis to our marketing team, who had limited technical knowledge. I used visual aids and analogies to explain the data trends, which helped them understand the implications for our strategy and led to a successful campaign launch.”

Behavioral Questions

1. Tell me about a time you faced a conflict while working on a team. How did you handle it?

This question assesses your interpersonal skills and ability to work collaboratively.

How to Answer

Use the STAR method (Situation, Task, Action, Result) to structure your response, focusing on your role in resolving the conflict.

Example

“During a project, there was a disagreement about the direction of our analysis. I facilitated a meeting where each team member could express their views. By encouraging open communication, we reached a consensus that combined our ideas, ultimately leading to a more robust analysis.”

2. How do you prioritize your work when managing multiple projects?

This question evaluates your organizational skills and ability to manage time effectively.

How to Answer

Discuss your approach to prioritization, including any tools or methods you use to stay organized.

Example

“I use a project management tool to track deadlines and progress. I prioritize tasks based on their impact on project goals and deadlines, ensuring that I allocate time effectively to meet all commitments.”

3. Describe a situation where you had to learn a new skill quickly. How did you approach it?

This question assesses your adaptability and willingness to learn.

How to Answer

Share a specific example of a skill you learned rapidly, focusing on your learning strategies and the outcome.

Example

“When I needed to learn R for a project, I dedicated time each day to online courses and practical exercises. I also reached out to colleagues for tips and best practices, which helped me become proficient enough to contribute effectively within a few weeks.”

4. What motivates you to work in the healthcare industry?

This question gauges your passion for the field and alignment with the company’s mission.

How to Answer

Express your motivations and how they connect to Eli Lilly’s goals and values.

Example

“I am motivated by the opportunity to make a tangible difference in patients’ lives. Working in healthcare allows me to apply my data science skills to solve real-world problems, contributing to the development of life-changing medicines.”

5. Why do you want to work at Eli Lilly?

This question assesses your knowledge of the company and your fit within its culture.

How to Answer

Discuss specific aspects of Eli Lilly that resonate with you, such as its mission, values, or innovative projects.

Example

“I admire Eli Lilly’s commitment to innovation and patient care. The opportunity to work with advanced analytics to improve healthcare outcomes aligns perfectly with my professional goals and personal values.”