At Interview Query, we’re here to guide you through the interview process for Pfizer. Pfizer is a leading global biopharmaceutical company committed to advancing wellness, prevention, treatments, and cures for diseases across various therapeutic areas. With a rich history of innovation, Pfizer strives to deliver breakthroughs that change patients' lives.

The role of a Data Analyst at Pfizer focuses on leveraging data to drive operational excellence within the company's External Supply Strategy & Operational Excellence (ES S&OE) group. This position requires robust analytical skills, technical proficiency in data tools and languages, and the ability to manage complex data analysis projects. You'll have the opportunity to work in a dynamic environment, contributing to strategic decision-making and leading data-driven initiatives.

Our guide will walk you through the interview process, provide insights from previous candidates, and arm you with the knowledge to succeed. Let’s get started!

Submitting Your Application

The first step is to submit a compelling application that reflects your technical skills and interest in joining Pfizer as a Data Analyst. Whether you were contacted by a Pfizer recruiter or have taken the initiative yourself, carefully review the job description and tailor your CV according to the prerequisites.

Tailoring your CV may include identifying specific keywords that the hiring manager might use to filter resumes and crafting a targeted cover letter. Furthermore, don’t forget to highlight relevant skills and mention your work experiences.

Recruiter/Hiring Manager Call Screening

If your CV happens to be among the shortlisted few, a recruiter from the Pfizer Talent Acquisition Team will make contact and verify key details like your experiences and skill level. Behavioral questions may also be a part of the screening process.

Questions like "What is something that I wouldn’t want to do or work on?" or "Do you prefer group projects or working alone?" might arise. The whole recruiter call should take about 30 minutes.

Technical Virtual Interview

Successfully navigating the recruiter round will present you with an invitation for the technical screening round. This round is conducted through virtual means, including video conference and screen sharing. Questions in this 1-hour long interview stage may revolve around Pfizer's data systems, ETL pipelines, and SQL queries.

You might also encounter situational and behavioral questions such as "How did you handle conflict with another colleague?" It is common for hiring managers to try to make you comfortable before the interview starts, acknowledging the anxiety-inducing nature of the process.

Onsite Interview Rounds

If you pass the technical round, you will be invited to attend the onsite interview loop. Multiple interview rounds will be conducted during your day at the Pfizer office. Your technical skills, including programming and database proficiency, will be assessed against other candidates throughout these interviews.

A typical onsite experience includes thorough interviews with around six hiring managers. Situational and behavioral questions will be prominent, and you may also have to present your take-home exercises or case studies if assigned.

Quick Tips For Pfizer Data Analyst Interviews

• Know Pfizer's Mission: Pfizer has an unwavering commitment to the quality and delivery of safe and effective products to patients. Understand how your role as a Data Analyst will contribute to this mission.

• Be Prepared for Behavioral Questions: Pfizer interviews include behavioral and situational questions. Reflect on past experiences and be ready to discuss how you have handled conflicts, worked in teams, or managed projects.

• Highlight Technical Skills: Your technical expertise, particularly in data models, database design, analytics, and visualization tools like Tableau, Spotfire, or Power BI, will be crucial. Brush up on these areas and be prepared to demonstrate your proficiency.

Typically, interviews at Pfizer vary by role and team, but commonly Data Analyst interviews follow a fairly standardized process across these question topics.

• How would you build a fraud detection model using a dataset of 600,000 credit card transactions? 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.

• How does random forest generate the forest and why use it over logistic regression? Explain the process by which random forest generates its forest. Additionally, discuss why one might choose random forest over logistic regression for certain tasks.

• When would you use a bagging algorithm versus a boosting algorithm? Compare two machine learning algorithms. Describe scenarios where you would use a bagging algorithm versus a boosting algorithm, and provide examples of the tradeoffs between the two.

• How would you evaluate and compare two credit risk models for personal loans?

• Identify the type of model your co-worker developed to determine loan eligibility.
• Given that personal loans are monthly installments, describe how you would measure the difference between two credit risk models within a timeframe.

• List the metrics you would track to measure the success of the new model.

• How would you explain linear regression to different audiences? 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.

• Create a function 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.

• Develop a function 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.

• Create a function to determine if a string is a palindrome. Given a string, write a function to determine if it is a palindrome. A palindrome reads the same forwards and backwards.

• Write a query to find users currently "Excited" and never "Bored" with a campaign. 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.

• Develop a function 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. The linked list is represented as a dictionary with value and next keys. If the list is empty, you'll receive None.

• Would you think there was anything fishy about the results of an A/B test with 20 variants? Your manager ran an A/B test with 20 different variants and found one significant result. Would you suspect any issues with these results?

• What considerations should be made when testing hundreds of hypotheses with many t-tests? You are testing hundreds of hypotheses using multiple t-tests. What factors should you consider to ensure the validity of your results?

• How would you generate a daily report and evaluate campaign performance for the first 7 days? 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.

• How would you investigate if a redesigned email campaign led to an increase in conversion rates? 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?

• What kind of analysis would you conduct to recommend UI changes for a community forum app? 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?

• Would you think there was anything fishy about the results of an A/B test with 20 variants? Your manager ran an A/B test with 20 different variants and found one significant result. Would you suspect any issues with the results?

• What is the downside of only using the R-Squared ((R^2)) value to determine a relationship between two variables? 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?

• Is a coin that comes up tails 8 times and heads twice in 10 flips fair? You flip a coin 10 times, resulting in 8 tails and 2 heads. Is this coin fair?

• How would you explain what a p-value is to someone who is not technical? Explain the concept of a p-value in simple terms to someone without a technical background.

• What’s the probability that (2X > Y) given two independent standard normal random variables (X) and (Y)? Given two independent standard normal random variables (X) and (Y), calculate the probability that (2X > Y).

What is the average salary for a Data Analyst at Pfizer?

Q: What is the interview process for a Data Analyst position at Pfizer like? The interview process typically starts with a phone interview with an HR representative followed by situational and behavioral questions. Usually, there is one or two rounds of interviews, which may involve technical assessments and a discussion with several managers. The hiring team aims to make candidates feel comfortable throughout the process.

Q: What responsibilities does a Data Analyst at Pfizer have? A Data Analyst at Pfizer will support strategy development, develop and implement databases, data analytics, and visualization strategies to optimize analytical efficiency and quality. They will also maintain and clean data, lead data governance, and collaborate with various internal and external stakeholders to drive operational excellence and contribute to key business decisions.

Q: What qualifications are required for the Data Analyst role at Pfizer? Must-have qualifications include a Bachelor's degree and 10 years of experience in a regulated industry, with proven expertise as a data analyst. Candidates should have excellent analytical skills, database management experience, and proficiency in programming languages like Python and SQL, as well as visualization tools such as Tableau and Power BI.

Q: What is Pfizer's work environment like for Data Analysts? The work environment at Pfizer is fast-paced and dynamic, providing opportunities to respond to multiple business needs with urgency and accuracy. The role involves extensive computer use and may require travel up to 40% of the time, depending on the business needs.

Q: What makes Pfizer an attractive employer for Data Analysts? Pfizer offers a competitive salary range, comprehensive benefits including 401(k) plans with matching contributions, paid leave, and health benefits. The company also provides opportunities for professional development and career growth within a supportive and collaborative work culture.

As the pharmaceutical industry leans heavily on data to drive innovation and operational excellence, Pfizer is at the forefront, seeking dynamic and skilled data analysts to join their team. By honing in on your analytical capabilities, mastering situational and behavioral interviews, and showcasing your adaptability in a fast-paced environment, you can position yourself as the standout candidate for Pfizer's Data Analyst role.

If you're looking to explore more about Pfizer's interview process, consider examining commonly asked Pfizer interview questions, along with valuable tips to excel in your interviews. Additionally, delving into the strategic goals and key responsibilities tailored for this role can give you a competitive edge.

Don't miss out on the opportunity to contribute to a company where your work directly impacts patient well-being and global healthcare advancements. Good luck with your interview, and here's to your success with Pfizer!