Change Healthcare Data Analyst Interview Questions + Guide in 2025

Change Healthcare is a leader in healthcare technology, dedicated to transforming how healthcare is delivered and managed through innovative solutions.

The Data Analyst role at Change Healthcare involves leveraging data to support the ClaimsXten Portfolio customers and their leadership teams, facilitating the adoption and utilization of editing solutions. Key responsibilities include designing and implementing analytic solutions, conducting savings calculations, forecasting revenue, and managing dashboard and invoicing processes. Candidates are expected to have a strong background in analytics, finance, and claims processing, complemented by skills in SQL, Excel, and data visualization. A great fit for this position will demonstrate effective communication skills, a customer-focused mindset, and the ability to analyze trends to provide actionable insights, all aligned with Change Healthcare's commitment to operational efficiency and innovation.

This guide will help you prepare for your interview by providing insights into the role and the types of skills and experiences you should emphasize.

The interview process for a Data Analyst position at Change Healthcare is structured to assess both technical skills and cultural fit. It typically consists of several rounds, each designed to evaluate different aspects of your qualifications and experience.

1. Initial HR Screening

The first step in the interview process is an initial screening conducted by an HR representative. This is usually a 30-minute phone interview where the recruiter will ask a series of predetermined questions. The focus will be on your background, experience, and understanding of the role. This is also an opportunity for you to learn more about Change Healthcare's culture and values.

2. Technical Interview

Following the HR screening, candidates typically undergo a technical interview, which lasts about an hour. This interview is often conducted via video call and focuses on your technical skills, particularly in SQL and data analysis. Expect questions that relate to your resume, as well as practical SQL problems that test your ability to write and execute queries. The interviewer may also explore your analytical thinking and problem-solving skills through scenario-based questions.

3. Onsite Interview

The final stage of the interview process is an onsite interview, which may also be conducted virtually. This round is more comprehensive and includes multiple components. Candidates are usually required to present a sample of their previous data analysis work, demonstrating their analytical capabilities and communication skills. Additionally, you may face questions related to market segmentation and a case study that assesses your ability to apply analytical concepts to real-world scenarios. This round is crucial as it allows the interviewers to gauge your fit within the team and your ability to handle client-facing responsibilities.

As you prepare for your interview, consider the specific skills and experiences that will be relevant to the questions you may encounter. Next, we will delve into the types of questions that are commonly asked during this interview process.

Here are some tips to help you excel in your interview.

Understand the Role and Its Impact

Before your interview, take the time to deeply understand the responsibilities of a Data Analyst at Change Healthcare. This role is not just about crunching numbers; it involves working closely with clients to design and implement analytic solutions that drive business decisions. Familiarize yourself with the specific tools and methodologies used in claims editing and processing, as well as the importance of financial forecasting and revenue reconciliation in the healthcare sector. This knowledge will allow you to speak confidently about how your skills align with the company's needs.

Prepare for Technical Questions

Given the emphasis on SQL and analytics in this role, ensure you are well-prepared to demonstrate your technical skills. Brush up on writing and executing SQL queries, as well as your proficiency in Excel for data analysis. Be ready to discuss your previous experiences with data analysis, particularly in the context of claims processing or healthcare analytics. Practice articulating your thought process when solving technical problems, as interviewers will be looking for your analytical reasoning and problem-solving abilities.

Showcase Your Communication Skills

As a Data Analyst, you will be required to communicate complex data insights to both technical and non-technical stakeholders. Prepare to demonstrate your verbal and written communication skills during the interview. You might be asked to explain a past project or analysis you conducted, so practice summarizing your work in a clear and concise manner. Highlight any experiences where you successfully led requirements sessions or collaborated with cross-functional teams, as these will showcase your ability to engage with clients and internal stakeholders effectively.

Be Ready for Case Studies and Presentations

Expect to encounter case study questions or be asked to present a previous data analysis project. This is an opportunity to showcase your analytical skills and your ability to derive actionable insights from data. Choose a project that highlights your strengths, particularly in areas relevant to Change Healthcare, such as savings calculations or trend analysis. Structure your presentation to clearly outline the problem, your approach, the results, and the impact of your findings. This will demonstrate your ability to think critically and communicate effectively.

Embrace the Company Culture

Change Healthcare values diversity, equity, and inclusion, so be prepared to discuss how you can contribute to this culture. Reflect on your past experiences working in diverse teams or how you have advocated for inclusivity in your previous roles. Showing that you align with the company’s values will not only help you stand out but also demonstrate that you are a good cultural fit for the organization.

Follow Up Thoughtfully

After your interview, send a thoughtful follow-up email thanking your interviewers for their time. Use this opportunity to reiterate your enthusiasm for the role and briefly mention a key point from your discussion that resonated with you. This not only shows your professionalism but also reinforces your interest in the position.

By preparing thoroughly and aligning your skills and experiences with the expectations of the role, you will position yourself as a strong candidate for the Data Analyst position at Change Healthcare. Good luck!

In this section, we’ll review the various interview questions that might be asked during a Data Analyst interview at Change Healthcare. The interview process will likely focus on your analytical skills, experience with SQL, and your ability to communicate effectively with clients and stakeholders. Be prepared to discuss your past experiences, particularly those that relate to claims editing, data analysis, and financial forecasting.

SQL and Data Management

1. Can you describe your experience with writing SQL queries? What types of queries have you executed?

This question assesses your technical proficiency with SQL, which is crucial for the role.

How to Answer

Discuss specific SQL queries you have written, such as SELECT statements, JOINs, or aggregate functions. Highlight any complex queries that demonstrate your ability to manipulate and analyze data effectively.

Example

“I have extensive experience writing SQL queries for data extraction and analysis. For instance, I frequently use JOINs to combine data from multiple tables to generate comprehensive reports. One complex query I wrote involved aggregating sales data by region and product category, which helped my team identify key trends in our sales performance.”

2. How do you ensure the accuracy and integrity of the data you analyze?

This question evaluates your attention to detail and understanding of data quality.

How to Answer

Explain the methods you use to validate data, such as cross-referencing with other data sources or implementing data cleaning techniques.

Example

“To ensure data accuracy, I implement a multi-step validation process. First, I cross-check data against original sources to identify discrepancies. Then, I use data cleaning techniques to remove duplicates and correct errors. This rigorous approach has consistently resulted in high-quality data for analysis.”

3. Describe a time when you had to analyze a large dataset. What tools did you use, and what was the outcome?

This question assesses your experience with data analysis tools and your ability to derive insights from large datasets.

How to Answer

Discuss the tools you used (e.g., SQL, Excel, or data visualization software) and the insights you gained from the analysis.

Example

“I once analyzed a dataset containing over a million records using SQL and Excel. I utilized pivot tables to summarize the data and identify trends. The analysis revealed a significant drop in customer retention rates, prompting my team to implement targeted marketing strategies that ultimately improved retention by 15%.”

4. How do you approach creating reports and dashboards for stakeholders?

This question evaluates your ability to communicate data insights effectively.

How to Answer

Describe your process for gathering requirements, designing reports, and ensuring they meet stakeholder needs.

Example

“When creating reports and dashboards, I start by meeting with stakeholders to understand their specific needs and objectives. I then design the report layout, ensuring it is user-friendly and visually appealing. After presenting the initial draft, I gather feedback and make necessary adjustments to ensure the final product effectively communicates the insights.”

Analytical Skills

1. Can you explain the concept of financial forecasting and how you have applied it in your previous roles?

This question assesses your understanding of financial forecasting, which is relevant to the role.

How to Answer

Discuss your experience with financial modeling and the methods you used for forecasting.

Example

“I have applied financial forecasting in several projects by developing models that incorporate historical data and market trends. For instance, I created a revenue forecast model for a new product launch, which helped the leadership team make informed decisions about resource allocation and marketing strategies.”

2. Describe a situation where you identified a trend or anomaly in data. What steps did you take to investigate it?

This question evaluates your analytical thinking and problem-solving skills.

How to Answer

Explain the steps you took to analyze the data, the tools you used, and the outcome of your investigation.

Example

“While analyzing client savings data, I noticed an unexpected spike in costs for a specific service. I used SQL to drill down into the data and discovered that a recent policy change had led to increased claims. I presented my findings to the operations team, which allowed them to adjust their strategy and mitigate the impact.”

3. How do you prioritize multiple projects with competing deadlines?

This question assesses your time management and organizational skills.

How to Answer

Discuss your approach to prioritization, including any tools or methods you use to manage your workload.

Example

“I prioritize projects by assessing their urgency and impact on the business. I use project management tools to track deadlines and progress. For instance, when faced with multiple deadlines, I break down tasks into smaller milestones and allocate time accordingly, ensuring that I meet all deadlines without compromising quality.”

4. What metrics do you consider most important when evaluating the success of a data analysis project?

This question evaluates your understanding of key performance indicators (KPIs) relevant to data analysis.

How to Answer

Discuss the metrics you track and why they are important for measuring success.

Example

“I consider metrics such as accuracy, timeliness, and stakeholder satisfaction as key indicators of a successful data analysis project. For example, I track the accuracy of my reports by comparing them against actual outcomes, and I gather feedback from stakeholders to ensure the insights provided meet their needs and expectations.”