Eli Lilly And Company is a global healthcare leader focused on discovering and delivering life-changing medicines to improve patient outcomes worldwide.
As a Data Analyst at Eli Lilly, you will play a pivotal role in ensuring the quality and integrity of critical data within the company's manufacturing and supply chain processes. Your key responsibilities will include managing master data sets in SAP and other systems, creating and maintaining standard operating procedures, and collaborating with cross-functional teams to support data change requests and continuous improvement initiatives. The ideal candidate will possess a strong understanding of supply chain principles, proficiency in data analysis tools including SAP and Excel, and an ability to work through ambiguity to drive solutions. Traits such as attention to detail, excellent organizational skills, and the ability to communicate effectively with diverse teams will set you apart in this role.
This guide will help you prepare effectively for your interview by equipping you with insights into the role's expectations and the competencies that Eli Lilly values most.
In this section, we’ll review the various interview questions that might be asked during a Data Analyst interview at Eli Lilly and Company. The interview process will likely focus on your technical skills, experience with data management systems, and your ability to work collaboratively in a team environment. Be prepared to discuss your past experiences, technical knowledge, and how you can contribute to the company's mission of improving lives through data-driven insights.
Understanding SQL is crucial for a Data Analyst role, and being able to articulate the differences between JOIN types demonstrates your technical proficiency.
Discuss the various types of JOINs (INNER, LEFT, RIGHT, FULL) and provide scenarios where each would be applicable.
“An INNER JOIN returns only the rows where there is a match in both tables, which is useful when you only want to see records that have corresponding entries. A LEFT JOIN, on the other hand, returns all records from the left table and matched records from the right table, which is helpful when you want to include all entries from one dataset regardless of matches.”
Data cleaning is a critical part of data analysis, and this question assesses your practical experience.
Outline the specific steps you took to clean the data, such as handling missing values, removing duplicates, and standardizing formats.
“In my previous role, I worked with a dataset that had numerous missing values and inconsistencies. I first identified the missing entries and decided to fill them with the mean for numerical columns. I also standardized date formats and removed any duplicate records to ensure the dataset was clean and ready for analysis.”
This question evaluates your attention to detail and your methods for maintaining data quality.
Discuss the processes you follow to validate your data and the tools you use to check for errors.
“I always cross-verify my findings with multiple sources and use automated scripts to check for anomalies in the data. Additionally, I document my analysis process thoroughly to ensure that others can replicate my results and verify the accuracy of the data.”
Data visualization is key in presenting your findings, and this question assesses your familiarity with various tools.
Mention the tools you have used (e.g., Tableau, Power BI, or Python libraries) and explain your preference based on your experiences.
“I have extensive experience with Tableau for creating interactive dashboards, which I find very user-friendly. I also use Python’s Matplotlib and Seaborn libraries for more customized visualizations. I prefer Tableau for its ease of use and ability to quickly share insights with stakeholders.”
This question assesses your problem-solving skills and resilience.
Describe the challenge, the actions you took to address it, and the outcome.
“During a project, I discovered that the data I was using was outdated, which could have led to incorrect conclusions. I quickly communicated this to my team and proposed a new data source. By collaborating with the data engineering team, we were able to update the dataset in time for our deadline, ensuring the accuracy of our analysis.”
This question evaluates your time management and organizational skills.
Discuss your approach to prioritization, such as using project management tools or methods like the Eisenhower Matrix.
“I prioritize my tasks based on deadlines and the impact of each project. I use tools like Trello to keep track of my tasks and regularly reassess my priorities to ensure I’m focusing on the most critical projects first.”
This question assesses your interpersonal skills and ability to work in a team.
Explain the situation, how you approached the team member, and the resolution.
“I once worked with a team member who was resistant to feedback. I scheduled a one-on-one meeting to discuss our project goals and listened to their concerns. By fostering open communication, we were able to find common ground and improve our collaboration moving forward.”
This question gauges your motivation and alignment with the company’s values.
Express your admiration for the company’s mission and how your skills align with their goals.
“I am passionate about using data to drive decisions that improve healthcare outcomes. Eli Lilly’s commitment to innovation and patient care resonates with my values, and I am excited about the opportunity to contribute to meaningful projects that make a difference in people’s lives.”
Here are some tips to help you excel in your interview.
Before your interview, take the time to deeply understand the responsibilities of a Data Analyst at Eli Lilly. Familiarize yourself with how the role contributes to the overall mission of the company, particularly in the context of healthcare and pharmaceuticals. Be prepared to discuss how your skills in data management and analysis can support the company's goals of improving patient outcomes and operational efficiency.
Given the emphasis on technical skills in the interview process, ensure you are well-versed in Python, SQL, and SAP. Review common data manipulation tasks and be ready to solve basic programming problems on the spot. Practice coding challenges that involve data analysis and manipulation, as these are likely to come up during the technical portion of the interview.
When discussing your background, focus on your internships and any relevant projects that showcase your analytical skills. Be specific about your contributions and the impact of your work. Use the STAR (Situation, Task, Action, Result) method to structure your responses, which will help you articulate your experiences clearly and effectively.
Eli Lilly values collaboration and communication, so be prepared to discuss how you work with others. Share examples of how you've successfully collaborated with cross-functional teams or resolved conflicts. Highlight your ability to communicate complex data insights to non-technical stakeholders, as this is crucial in a role that supports various departments.
Expect behavioral questions that assess your problem-solving abilities and adaptability. Prepare to discuss times when you faced challenges in your work or academic projects, how you approached those challenges, and what you learned from the experience. This will demonstrate your resilience and ability to learn from setbacks.
Eli Lilly places a strong emphasis on caring and community involvement. Be prepared to discuss why you want to work for the company and how your values align with theirs. Mention any initiatives or programs at Lilly that resonate with you, and express your eagerness to contribute to a culture that prioritizes both employee well-being and patient care.
During the interview, practice active listening. This means not only hearing the questions but also understanding the underlying concerns or objectives behind them. This will help you provide more relevant and thoughtful responses, demonstrating your engagement and interest in the conversation.
After the interview, send a thank-you email to your interviewers. In your message, reiterate your interest in the position and mention specific points from the interview that you found particularly engaging. This not only shows your appreciation but also reinforces your enthusiasm for the role and the company.
By following these tips, you will be well-prepared to make a strong impression during your interview at Eli Lilly. Good luck!
The interview process for a Data Analyst position at Eli Lilly is structured to assess both technical skills and cultural fit within the organization. Candidates can expect a multi-step process that includes various types of interviews and assessments.
The process typically begins with an initial screening, which may be conducted via phone or video call. During this stage, a recruiter will discuss the role, the company culture, and the candidate's background. This is an opportunity for the recruiter to gauge the candidate's interest in the position and to assess their basic qualifications, including relevant experience and skills in data analysis tools such as Python and SQL.
Following the initial screening, candidates may be required to complete a technical assessment. This could involve a written exam that tests aptitude and includes programming questions related to data analysis. The assessment is designed to evaluate the candidate's proficiency in key technical areas relevant to the role, such as data manipulation, statistical analysis, and familiarity with software like SAP or other data management systems.
Candidates who pass the technical assessment will typically move on to a behavioral interview. This interview focuses on the candidate's past experiences, problem-solving abilities, and how they handle various workplace situations. Questions may revolve around teamwork, conflict resolution, and adaptability, providing insight into how the candidate aligns with Eli Lilly's values and culture.
In addition to the behavioral interview, candidates may also participate in a more in-depth technical interview. This session often involves discussions with team members or managers who will assess the candidate's technical knowledge and practical application of data analysis concepts. Candidates should be prepared to answer questions about their previous projects, methodologies used, and specific technical challenges they have faced.
The final stage of the interview process may include a wrap-up interview with senior management or team leads. This interview often combines both technical and behavioral elements, allowing the interviewers to evaluate the candidate's overall fit for the team and the organization. Candidates may be asked to discuss their long-term career goals and how they envision contributing to Eli Lilly's mission.
As you prepare for your interview, it's essential to familiarize yourself with the types of questions that may be asked during each stage of the process.
max_substring
to find the maximal substring shared by two strings.Given two strings, string1
and string2
, write a function max_substring
to return the maximal substring shared by both strings. If there are multiple max substrings with the same length, return any one of them.
moving_window
to find the moving window average of a list of numbers.Given a list of numbers nums
and an integer window_size
, write a function moving_window
to find the moving window average.
Given a string, write a function to determine if it is a palindrome. A palindrome reads the same forwards and backward.
You have a table of users’ impressions of ad campaigns over time. Each impression_id
consists of values of user engagement specified by Excited
, OK
, and Bored
. Write a query to find all users that are currently “Excited” and have never been “Bored” with a campaign.
search_list
to check if a target value is in a linked list.Write a function, search_list
, that returns a boolean indicating if the target
value is in the linked_list
or not. You receive the head of the linked list, which is a dictionary with value
and next
keys. If the linked list is empty, you’ll receive None
.
You are analyzing how well a model fits the data and want to determine a relationship between two variables. What are the limitations of relying solely on the R-squared value?
You flip a coin 10 times, resulting in 8 tails and 2 heads. Is this coin fair?
Describe what a p-value is in simple terms for someone without a technical background.
Given two independent standard normal random variables (X) and (Y), calculate the probability that (2X > Y).
Imagine you work at a major credit card company and are given a dataset of 600,000 credit card transactions. Describe your approach to building a fraud detection model in the comments.
Explain the process of how a random forest generates its forest. Additionally, discuss why one might choose random forest over other algorithms such as logistic regression.
Compare two machine learning algorithms. Provide an example of when you would use a bagging algorithm versus a boosting algorithm, and discuss the tradeoffs between the two.
Explain the concept of linear regression to three different audiences: a child, a first-year college student, and a seasoned mathematician. Tailor your explanations to the understanding level of each audience.
Your manager ran an A/B test with 20 different variants and found one significant result. Would you suspect any issues with these results?
You are testing hundreds of hypotheses using multiple t-tests. What factors should you consider to ensure the validity of your results?
Given a schema representing advertiser campaigns and impressions, generate a daily report for the first 7 days. Evaluate campaign performance and identify which promos need attention using a specific heuristic.
A new marketing manager redesigned the new-user email journey, and conversion rates increased from 40% to 43%. However, the rate was previously 45% before dropping to 40%. How would you determine if the redesign caused the increase?
You have access to tables summarizing user event data for a community forum app. What analysis would you perform to recommend improvements to the user interface?
Here are a few tips for acing your Eli Lilly interview:
Understand Eli Lilly’s Mission: Familiarize yourself with Eli Lilly’s mission and core values. Be prepared to discuss how your skills and experiences align with their objectives, particularly in the pharmaceutical and healthcare sectors.
Be Data-Driven: Eli Lilly places a strong emphasis on data-driven decision-making. Brush up on your knowledge of statistics, SQL, and data visualization tools like Tableau or PowerBI.
Technical and Behavioral Proficiency: Be ready for a mix of technical questions related to Python, R, SQL, and data analysis. Expect behavioral questions to understand your problem-solving abilities, team collaboration, and adaptability.
According to Glassdoor, data analysts at Eli Lilly and Company earn between $79K to $120K per year, with an average of $97K per year.
For a Data Analyst role at Eli Lilly and Company, proficiency in Python and SQL is essential. Additional skills include data visualization, data storytelling, web-based data visualization using d3, and familiarity with tools like SAP and MES. Understanding advanced analytics methods, machine learning, and statistical techniques is also important.
Eli Lilly and Company fosters career growth through continuous learning, feedback, and collaboration. The company encourages data analysts to stay current with the latest methods, participate in design reviews, and be actively involved in problem-solving with diverse business partners. There are also numerous employee resource groups and opportunities for internal and external consulting experience.
Eli Lilly and Company prides itself on a culture that combines caring with discovery. The company focuses on improving global health, valuing innovation, and giving back to communities. Employees are encouraged to put people first, collaborate effectively, and strive for excellence in their work.
The interview process for the Data Analyst position at Eli Lilly and Company is systematic and straightforward, focusing on both technical capabilities and soft skills.
If you want more insights about the company, check out our main Eli Lilly And Company Interview Guide, where we have covered many interview questions that could be asked. We’ve also created interview guides for other roles, such as software engineer and data analyst, where you can learn more about Eli Lilly and Company’s interview process for different positions.
You can also check out all our company interview guides for better preparation, and if you have any questions, don’t hesitate to reach out to us.
Good luck with your interview!