Cooper University Health Care is a leading healthcare provider renowned for its commitment to quality patient care, medical education, and research. It is one of the premier academic health systems in the United States, and its strong focus on innovation forms the backbone of its extensive healthcare services and community care initiatives.

Joining Cooper University Health Care as a Data Scientist means you will play a pivotal role in leveraging data to drive decision-making and improve patient outcomes. This position demands a high level of proficiency in data analysis, statistical modeling, and machine learning, along with strong problem-solving skills. As a Data Scientist, you will work on diverse projects ranging from predictive analytics to operational efficiency, interrogating large datasets to inform strategic initiatives.

Getting prepared for this role is crucial. Interview Query offers this guide to help you navigate the interview process, understand what to expect, and excel in your forthcoming interviews.

Submitting Your Application

The first step is to submit a compelling application that reflects your technical skills and interest in joining Cooper University Health Care as a Data Scientist. Whether you were contacted by a Cooper University Health Care 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 Cooper University Health Care 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.

In some cases, the Cooper University Health Care hiring manager stays present during the screening round to answer your queries about the role and the company itself. They may also indulge in surface-level technical and behavioral discussions.

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. Technical screening for the Cooper University Health Care Data Scientist role is usually conducted through virtual means, including video conference and screen sharing. Questions in this 1-hour long interview stage may revolve around the healthcare data systems, ETL pipelines, and SQL queries.

Given the nature of the position, take-home assignments regarding healthcare data analytics, machine learning model building, and data visualization are incorporated. Apart from these, your proficiency against hypothesis testing, probability distributions, and machine learning fundamentals may also be assessed during the round.

Depending on the seniority of the position, case studies and similar real-scenario problems may also be assigned.

Onsite Interview Rounds

Followed by a second recruiter call outlining the next stage, you’ll be invited to attend the onsite interview loop. Multiple interview rounds, varying with the role, will be conducted during your day at the Cooper University Health Care office. Your technical prowess, including programming and ML modeling capabilities, will be evaluated against the finalized candidates throughout these interviews.

If you were assigned take-home exercises, a presentation round may also await you during the onsite interview for the Data Scientist role at Cooper University Health Care.

Quick Tips For Cooper University Health Care Data Scientist Interviews

• Understand Healthcare Data: Brush up on your knowledge of healthcare-specific datasets, HIPAA compliance, and the unique challenges posed by medical data.
• Be Data Driven: Cooper University Health Care values how well you can provide actionable insights through data science. Focus on enhancing your skills in statistics, probability, and machine learning.
• Showcase Your Technical Expertise: Demonstrate your proficiency in SQL, Python, R, and other relevant tools. Practical projects or experiences in the healthcare field can give you an edge.

Typically, interviews at Cooper University Health Care vary by role and team, but commonly Data Scientist interviews follow a fairly standardized process across these question topics.

• How would you interpret coefficients of logistic regression for categorical and boolean variables? Explain how to interpret the coefficients of logistic regression when dealing with categorical and boolean variables.

• How would you design a machine learning model to classify major health issues based on health features? You work as a machine learning engineer for a health insurance company. Design a model that classifies if an individual will undergo major health issues based on a set of health features.

• What metrics and statistical methods would you use to identify dishonest users in a sports app? You work for a company with a sports app that tracks running, jogging, and cycling data. Formulate a method to identify users who might be cheating, such as driving a car while claiming to be on a bike ride. Specify the metrics and statistical methods you would analyze.

• Develop a function str_map to determine if a one-to-one correspondence exists between characters of two strings at the same positions. Given two strings, string1, and string2, write a function str_map to determine if there exists a one-to-one correspondence (bijection) between the characters of string1 and string2.

• Build a logistic regression model from scratch using gradient descent and log-likelihood as the loss function. Create a logistic regression model from scratch without an intercept term. Use basic gradient descent (with Newton's method) for optimization and the log-likelihood as the loss function. Do not include a penalty term. You may use numpy and pandas but not scikit-learn. Return the parameters of the regression.

• Why are job applications decreasing despite stable job postings? You are analyzing a job board where the number of job postings per day has remained constant, but the number of applicants has been steadily decreasing. What could be the reasons for this trend?

• What would you do if friend requests on Facebook are down 10%? A product manager at Facebook informs you that friend requests have decreased by 10%. What steps would you take to investigate and address this issue?

• How would you assess the validity of a .04 p-value in an AB test? Your company is running an AB test on a feature to increase conversion rates on the landing page. The PM reports a p-value of .04. How would you evaluate the validity of this result?

• How would you analyze the performance of a new LinkedIn feature without an AB test? LinkedIn has launched a feature allowing candidates to message hiring managers directly during the interview process. Due to engineering constraints, an AB test was not conducted. How would you analyze the feature's performance?

• Should Square hire a customer success manager or offer a free trial for a new product? You are in charge of Square's small business division. The CEO wants to hire a customer success manager for a new software product, while another executive suggests offering a free trial instead. What would be your recommendation?

• 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.

• How would you interpret coefficients of logistic regression for categorical and boolean variables? Explain how to interpret the coefficients of logistic regression when dealing with categorical and boolean variables.

• How would you tackle multicollinearity in multiple linear regression? Describe the methods you would use to address multicollinearity in a multiple linear regression model.

• How would you design a facial recognition system for employee clock-in and secure access? You work as an ML engineer for a large company that wants to implement a facial recognition system for employee clock-in, clock-out, and access to secure systems. The system should also accommodate temporary contract consultants. How would you design this system?

• How would you handle data preparation for building a machine learning model using imbalanced data? Explain the steps you would take to prepare data for building a machine learning model when dealing with imbalanced datasets.

What is the average salary for a Data Scientist at Cooper University Health Care?

Q: What is Cooper University Health Care?
Cooper University Health Care is a top-tier medical institution serving South Jersey and the Delaware Valley. It's known for its advanced medical technologies, comprehensive healthcare services, and a commitment to continuous medical education and research.

Q: What are the main responsibilities of a Data Scientist at Cooper University Health Care?
As a Data Scientist, you'll be tasked with extracting meaningful insights from large datasets to drive strategic decision-making. Responsibilities include building predictive models, developing data-driven solutions, performing data analysis, and collaborating with healthcare professionals to improve patient outcomes.

Q: What skills are required for the Data Scientist position?
The ideal candidate should possess strong analytical skills, proficiency in statistical software (such as R or Python), experience with machine learning algorithms, and knowledge of database management systems. Additionally, strong communication skills are essential for translating complex data insights to non-technical stakeholders.

Q: What is the interview process like for the Data Scientist position at Cooper University Health Care?
The interview process typically involves an initial phone screening, followed by technical interviews that assess your analytical and problem-solving skills. You may also be required to complete case studies or practical tests to demonstrate your ability to handle real-world data scenarios.

Q: How can I best prepare for the interview?
To prepare for the interview, familiarize yourself with Cooper University Health Care's mission and recent projects. Practice common data science interview questions on Interview Query, and review your experiences related to data analysis, machine learning, and healthcare analytics. Be ready to discuss how your skills can contribute to improving healthcare outcomes at Cooper University Health Care.

Embarking on a career as a Data Scientist at Cooper University Health Care offers a rewarding journey filled with innovation and growth. If you want more insights about the company, check out our main Cooper University Health Care Interview Guide, where we have covered many interview questions that could be asked. We've also created interview guides for other roles to help you understand their interview process comprehensively.

At Interview Query, we empower you to unlock your interview prowess with a comprehensive toolkit, equipping you with the knowledge, confidence, and strategic guidance to conquer every challenge in your Data Scientist interview. You can 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!