Werfen, founded in 1966, is a global leader in developing, manufacturing, and distributing specialized diagnostic instruments and data management solutions primarily for hospitals and clinical laboratories. The company's core business areas include Hemostasis, Acute Care, Autoimmunity diagnostics, and Original Equipment Manufacturing. With a strong focus on innovation, quality, and customer commitment, Werfen offers healthcare professionals valuable solutions to enhance patient care and improve hospital efficiency.
As a Data Scientist at Werfen, you will be a part of the Analytical team, utilizing machine learning and big data analysis to optimize product functionality. The role demands proficiency in programming languages such as Python, R, or MATLAB, and familiarity with machine learning techniques. If you are passionate about leveraging data to drive meaningful improvements and thrive in a dynamic environment, this guide is for you. Here, Interview Query walks you through the interview process, commonly asked questions, and valuable tips. Dive in to prepare effectively and excel in your Werfen interview journey.
The first step in securing a Data Scientist position at Werfen is to submit a compelling application that reflects your technical skills, academic success, and passion for improving healthcare efficiency. Whether you were contacted by a Werfen recruiter or have taken the initiative yourself, carefully review the job description and tailor your CV to meet the outlined responsibilities and qualifications.
Tailoring your CV may include identifying specific keywords that the hiring manager might use to filter resumes and drafting a targeted cover letter. Don’t forget to highlight relevant skills and mention your work experiences that align with Werfen's focus areas like diagnostic instruments, data management solutions, and machine learning.
If your CV is shortlisted, a recruiter from Werfen’s Talent Acquisition Team will reach out to verify key details like your experiences, skill set, and leadership potential. Prepare for potential behavioral questions as well.
In some cases, the hiring manager for the Data Scientist role may join the screening call to provide insights about the role and Werfen itself. Surface-level technical and behavioral discussions might also occur during this round.
The recruiter call typically takes about 30 minutes.
Passing the recruiter round will lead to an invitation for a technical screening round. This is usually conducted virtually via video conference and screen sharing. For the Data Scientist role, this 1-hour long interview may include questions revolving around Werfen’s data systems, machine learning techniques, statistical analysis, and big data.
You may be asked to solve problems and discuss your approach to optimizing data functionality and interpreting large datasets. Proficiency in programming languages such as Python, R, or MATLAB will be crucial during this round.
After a second recruiter call outlining the next steps, you’ll be invited to attend the onsite interview loop. Multiple interview rounds will be conducted during your visit to Werfen’s office, focusing on technical prowess and problem-solving abilities.
If you were given take-home exercises, you might also have a presentation round to discuss your findings. You may face multiple scenarios and case studies requiring you to propose innovative solutions relevant to Werfen’s diagnostic products.
To excel in your Werfen Data Scientist interviews, consider these tips:
Typically, interviews at Werfen vary by role and team, but commonly Data Scientist interviews follow a fairly standardized process across these question topics.
Write a function calculate_rmse
to calculate the root mean squared error of a regression model.
The function should take in two lists, one that represents the predictions y_pred
and another with the target values y_true
.
Write a query to get the last transaction for each day from a table of bank transactions.
Given a table of bank transactions with columns id
, transaction_value
, and created_at
representing the date and time for each transaction, write a query to get the last transaction for each day. The output should include the id of the transaction, datetime of the transaction, and the transaction amount. Order the transactions by datetime.
Write a function random_key
that returns a key at random with a probability proportional to the weights.
Given a dictionary with weights, write a function random_key
that returns a key at random with a probability proportional to the weights.
Write a function to get a sample from a standard normal distribution. Create a function to generate a sample from a standard normal distribution.
Write an efficient function nearest_entries
to find the closest element to N
in a sorted list and return surrounding elements.
Given a sorted list of integers ints
with no duplicates, write an efficient function nearest_entries
that takes in integers N
and k
and finds the element of the list that is closest to N
. Return that element along with the k
-next and k
-previous elements of the list.
How would you analyze the churn behavior of users on different Netflix pricing plans? Netflix has two pricing plans: $15/month or $100/year. An executive wants an analysis of the churn behavior for these plans. What metrics, graphs, and models would you use to provide an overarching view of subscription performance?
How would you predict which merchants DoorDash should acquire in a new market? As a data scientist at DoorDash, how would you build a model to predict which merchants the company should target for acquisition when entering a new market?
How would you value the benefit of keeping a hit TV series on Netflix? Netflix executives are considering renewing a deal for exclusive streaming rights to a hit TV series. The show has been on Netflix for a year. How would you approach valuing the benefit of keeping this show on the platform?
How would you measure and address the success of LinkedIn’s newsfeed ranking algorithm?
If some success metrics for the newsfeed algorithm are improving while others are declining, how would you approach this situation?
How would you determine the statistical significance of an AB test for a landing page redesign? We want to launch a redesign of a landing page to improve the click-through rate using an AB test. How would you infer if the results of the click-through rate were statistically significant?
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 a non-technical person. Use analogies or everyday examples to make the explanation clear and understandable.
How many more samples would we need to decrease the margin of error from 3 to 0.3? Given a sample size (n) with a margin of error of 3, calculate the additional number of samples required to reduce the margin of error to 0.3.
How would you determine if the results of an AB test on click-through rate are statistically significant? Describe the process of analyzing AB test results to determine if the observed differences in click-through rates are statistically significant. Include steps such as hypothesis testing and p-value calculation.
How would you build a model to predict which merchants DoorDash should acquire in a new market? As a data scientist at DoorDash, how would you develop a model to identify which merchants the company should target for acquisition when entering a new market?
How would you assign point values to letters in Spanish Scrabble without knowing Spanish? If tasked with building Scrabble for Spanish users and you don't know Spanish, how would you determine the point values for each letter?
Werfen, founded in 1966, is a global developer, manufacturer, and distributor of specialized diagnostic instruments, reagents, automation workcells, and data management solutions mainly used in hospitals and independent clinical laboratories. Our business lines encompass Hemostasis, Acute Care, Autoimmunity diagnostics, and Original Equipment Manufacturing.
Our North American Commercial Operations, as well as our Headquarters and Technology Center for Hemostasis and Acute Care Diagnostics, are based in Bedford, MA. We also have a Headquarters and Technology Center for Autoimmunity Diagnostics in San Diego, CA, and a Technology Center for Hemostasis and Blood Gas Reagents in Orangeburg, NY, along with a Technology Center for Whole Blood Hemostasis in San Diego, CA.
As a Data Scientist at Werfen, you will be part of the Analytical team, focusing on product improvement through machine learning. Responsibilities include performing big data analysis, developing code to extract useful information from products, and proposing new techniques based on statistical data. You'll need to be proficient with Python, familiar with machine learning techniques, and able to analyze and interpret numerical data from experiments.
You should be currently pursuing a B.S. in Computer Science, Biomedical Engineering, or Mathematics, with at least 2 college semesters completed. Additionally, strong analytical strength, creative problem-solving abilities, and proficiency with Microsoft tools like Word, Excel, and PowerPoint are essential.
To prepare for an interview at Werfen, research the company, practice common interview questions, and review your technical skills. Make sure to be ready to discuss your past experiences and how they relate to the position you are applying for. Use resources like Interview Query to practice and better your chances of landing the role.
If you're excited to join a team that is dedicated to innovation in the rapidly evolving field of specialized diagnostics, Werfen might just be the place for you. With a rich history since 1966 and a commitment to customer satisfaction, Werfen offers a dynamic environment where your skills in data science can directly impact hospital efficiency and patient care.
To further prepare for your interview, check out our comprehensive Werfen Interview Guide, where we've covered many interview questions you might encounter. Plus, explore interviews for other roles, such as data analyst or software engineer to get a broader perspective of the process.
At Interview Query, we provide you with the tools and insights to excel in your interviews, equipping you with the knowledge and confidence to succeed. Explore all our company interview guides for more preparation tips, and feel free to reach out if you have any questions.
Good luck with your interview!