Welcome to Veradigm, where our mission is transforming health through insightful and data-driven solutions. We address today's healthcare challenges by leveraging the power of research, analytics, and artificial intelligence (AI) to create scalable solutions benefiting biopharma, health plans, healthcare providers, health technology partners, and patients. As a Business Analyst at Veradigm, you'll support the IT ERP and HRIS environments, collaborating closely with business and IT leaders to define and implement strategies that drive business outcomes. If you're ready to join a dynamic team dedicated to revolutionizing healthcare, read on to learn about the interview process and commonly asked questions for this role on Interview Query.

Submitting Your Application

Welcome to Veradigm, where our Mission is transforming health, insightfully. Join the Veradigm team and help solve many of today's healthcare challenges being addressed by biopharma, health plans, healthcare providers, health technology partners, and the patients they serve.

At Veradigm, our primary focus is on harnessing the power of research, analytics, and artificial intelligence (AI) to develop scalable data-driven solutions that bring significant value to all healthcare stakeholders. Together, we can transform healthcare and enable smarter care for millions of people.

The first step to joining Veradigm as a Business Analyst is to submit a compelling application that reflects your technical skills and interest in the role. Carefully review the job description and tailor your CV according to the prerequisites. Highlight relevant skills and mention your work experiences, particularly in areas like applications development, business process management, and enterprise architecture.

Tailoring your CV may include identifying specific keywords that the hiring manager might use to filter resumes and crafting a targeted cover letter.

Recruiter/Hiring Manager Call Screening

If your CV is shortlisted, a recruiter from Veradigm will contact you to verify key details like your experiences and skill level. Behavioral questions may also be part of the screening process.

In some cases, the Veradigm Business Analyst hiring manager may join the screening round to discuss 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

Upon successfully navigating the recruiter round, you will be invited for the technical screening round. This usually includes video conference and screen sharing. Questions in this 1-hour long interview may revolve around data systems, analytics, integrations (API's, EIB's), and SQL queries.

For the Business Analyst roles at Veradigm, take-home assignments regarding product metrics, analytics, and data visualization might also be part of the process. Your proficiency in hypothesis testing, probability distributions, and other relevant skills may be assessed during this round.

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

Onsite Interview Rounds

Once the technical screening round is cleared, followed by another recruiter call outlining the next stage, you’ll be invited to attend the onsite interview loop. Multiple interview rounds will be conducted during your onsite day. Your technical prowess—including programming, system workflows, and problem-solving capabilities—will be evaluated.

If you were assigned take-home exercises, a presentation round may also be included during the onsite assessment.

Quick Tips For Veradigm Business Analyst Interviews

You should plan to brush up on any technical skills and try as many practice interview questions and mock interviews as possible. A few tips for acing your Veradigm interview include:

• Understand Veradigm’s Core Values: Veradigm focuses on transforming health through insights. Make sure you understand the company's mission and how your role fits within it.
• Demonstrate Technical Proficiency: The role requires a deep understanding of technical integrations, data analytics, and business process management. Highlight your expertise in these areas.
• Be Ready for Behavioral Questions: Veradigm values a positive and proactive attitude. Prepare to discuss scenarios where you engaged team members and collaborated with stakeholders to solve business needs.

Typically, interviews at Veradigm vary by role and team, but commonly Business Analyst 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. Discuss the meaning of these coefficients in the context of the model.

• How would you design a machine learning model to classify major health issues based on health features? As a machine learning engineer for a health insurance company, design a model that classifies whether an individual will undergo major health issues based on a set of health features. Describe the steps and considerations involved.

• What metrics and statistical methods would you use to identify dishonest users in a sports tracking app? For a sports app that tracks running, jogging, and cycling data, formulate a method to identify users who may be cheating (e.g., driving a car while claiming to bike). Specify the metrics you would analyze and the statistical methods you would use to detect anomalies indicative of dishonest behavior.

• 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 observe that the number of job postings per day has remained stable, but the number of applicants has been steadily decreasing. What could be causing 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%. How would you address this issue?

• How would you assess the validity of a .04 p-value in an AB test? Your company is running a standard control and variant AB test to increase conversion rates on the landing page. The PM finds 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 new feature allowing candidates to message hiring managers directly during the interview process. Due to engineering constraints, an AB test wasn't possible. How would you analyze the feature's performance?

• Customer success manager vs. free trial for Square's new product? The CEO of Square's small business division wants to hire a customer success manager for a new software product, while another executive suggests instituting 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? Describe the steps you would take to prepare data for building a machine learning model when dealing with imbalanced data.

If you're excited about transforming healthcare through the power of research, analytics, and artificial intelligence, Veradigm is the place for you. At Veradigm, you'll be joining a team committed to developing scalable data-driven solutions that positively impact millions of lives. Ready to bring your expertise in IT ERP and HRIS environments, project management, and process improvement to a company that values innovation and collaboration?

For more insights about Veradigm, check out our main Veradigm 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 Veradigm’s interview process for different positions.

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 Veradigm Business Analyst interview question and challenge.

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!