The Rawlings Group Business Intelligence Interview Guide

Getting ready for a Business Intelligence interview at The Rawlings Group? The Rawlings Group Business Intelligence interview process typically spans a wide range of question topics and evaluates skills in areas like data analysis, dashboard design, stakeholder communication, and data pipeline architecture. Interview preparation is especially important for this role, as candidates are expected to translate complex business requirements into actionable insights, optimize data workflows, and communicate findings clearly to both technical and non-technical audiences in a fast-paced, data-driven environment.

In preparing for the interview, you should:

• Understand the core skills necessary for Business Intelligence positions at The Rawlings Group.
• Gain insights into The Rawlings Group’s Business Intelligence interview structure and process.
• Practice real The Rawlings Group Business Intelligence interview questions to sharpen your performance.

At Interview Query, we regularly analyze interview experience data shared by candidates. This guide uses that data to provide an overview of the The Rawlings Group Business Intelligence interview process, along with sample questions and preparation tips tailored to help you succeed.

The Rawlings Group is a leading provider of specialized recovery services for the health insurance industry, established in 1977. The company pioneered the first subrogation outsourcing program for healthcare and has since expanded into medical claims, mass tort litigation, and pharmaceutical claims recovery. Today, The Rawlings Group focuses exclusively on helping health insurance clients recover funds, maintaining a reputation for delivering superior financial results. As a Business Intelligence professional, you will contribute to optimizing recovery operations and supporting data-driven decision-making that aligns with the company’s commitment to client success.

As a Business Intelligence professional at The Rawlings Group, you will be responsible for gathering, analyzing, and transforming data to support the company’s healthcare claims recovery operations. You will develop and maintain dashboards, generate reports, and provide actionable insights to business leaders and operational teams. Key tasks include identifying trends, optimizing processes, and supporting strategic initiatives through data-driven recommendations. By collaborating with IT, analytics, and business units, you help ensure data accuracy and improve decision-making across the organization, ultimately contributing to The Rawlings Group’s mission of delivering efficient and effective healthcare cost recovery solutions.

2.1 Stage 1: Application & Resume Review

The initial stage involves a thorough review of your application materials by the talent acquisition team, focusing on your experience with business intelligence, data analysis, dashboard development, and stakeholder communication. Candidates with demonstrated expertise in SQL, data visualization, ETL processes, and translating data insights for business impact are prioritized. To prepare, ensure your resume clearly highlights quantifiable achievements, relevant technical skills, and examples of cross-functional collaboration.

2.2 Stage 2: Recruiter Screen

In this stage, a recruiter will conduct a phone or video interview to discuss your background, motivation for applying, and alignment with the company’s mission. Expect questions about your interest in business intelligence, your understanding of The Rawlings Group’s industry, and your ability to communicate complex data concepts to non-technical audiences. Preparation should center on articulating your career story, research into the company’s services, and your approach to making data accessible.

2.3 Stage 3: Technical/Case/Skills Round

This round typically consists of one or more interviews led by business intelligence team members or a data manager. You’ll be assessed on your technical proficiency in SQL (including writing queries, aggregations, and pivot tables), data pipeline design, ETL workflows, and dashboard/report creation. Case studies or real-world scenarios may be presented, requiring you to analyze data, design solutions, and justify your approach. Brush up on translating business problems into analytical solutions, and practice explaining your reasoning for metric selection and experiment design.

2.4 Stage 4: Behavioral Interview

Behavioral interviews are conducted by team leads or potential cross-functional partners, evaluating your interpersonal skills, adaptability, and problem-solving mindset. You’ll be asked to share examples of overcoming data project hurdles, collaborating with stakeholders, and communicating insights to diverse audiences. Prepare by reflecting on past experiences where you resolved misaligned expectations, drove clarity for non-technical users, or adapted your communication style for different audiences.

2.5 Stage 5: Final/Onsite Round

The final stage often includes a panel or a series of interviews with senior leadership, analytics directors, and future teammates. This round may require you to present a business intelligence project or walk through a case study, demonstrating your ability to synthesize complex data, generate actionable insights, and tailor presentations to executive stakeholders. Focus on clarity, business impact, and your ability to lead discussions around data-driven decision making.

2.6 Stage 6: Offer & Negotiation

If successful, you’ll receive an offer from the talent acquisition team. This stage involves discussions on compensation, benefits, and start date. Be prepared to negotiate and clarify any questions regarding role expectations, growth opportunities, and team structure.

2.7 Average Timeline

The typical interview process for a Business Intelligence role at The Rawlings Group spans 3-5 weeks from initial application to offer. Fast-track candidates with highly relevant experience or internal referrals may progress within 2-3 weeks, while the standard process allows for a week between each stage to accommodate scheduling and project-based assessments. Take-home assignments or technical presentations may extend the timeline by several days.

Next, let’s explore the specific interview questions you may encounter throughout this process.

3.1 Data Analysis & Business Insights

Business Intelligence at The Rawlings Group centers on transforming raw data into actionable insights that drive strategic decisions. Expect questions that assess your ability to analyze datasets, design metrics, and communicate findings effectively to both technical and non-technical audiences.

3.1.1 How to present complex data insights with clarity and adaptability tailored to a specific audience
Focus on structuring your presentation based on stakeholder needs, using visualizations and storytelling to simplify technical findings. Tailor your language and examples to match the audience’s familiarity with data concepts.

3.1.2 Making data-driven insights actionable for those without technical expertise
Translate technical results into clear, business-relevant recommendations. Emphasize the impact of your findings and use analogies or visuals to bridge the gap between data and decision-making.

3.1.3 Demystifying data for non-technical users through visualization and clear communication
Describe how you leverage dashboards, infographics, or interactive reports to make data accessible. Highlight your approach to choosing the right visualization for the message and audience.

3.1.4 What metrics would you use to determine the value of each marketing channel?
Discuss key performance indicators such as conversion rates, cost per acquisition, and customer lifetime value. Explain how you would track, compare, and optimize channels based on business goals.

3.1.5 Which metrics and visualizations would you prioritize for a CEO-facing dashboard during a major rider acquisition campaign?
Prioritize high-impact metrics like acquisition rate, retention, and campaign ROI. Justify your choice of visualizations for executive clarity, focusing on trends and actionable insights.

3.2 Experimentation & A/B Testing

This area evaluates your ability to design, execute, and interpret experiments that inform business strategy. You’ll need to demonstrate statistical rigor and an understanding of how experimentation drives product and process improvements.

3.2.1 Assessing the market potential and then use A/B testing to measure its effectiveness against user behavior
Describe how you would estimate market opportunity and set up controlled tests to validate hypotheses. Highlight your approach to measuring user engagement and interpreting test results.

3.2.2 Write a query to calculate the conversion rate for each trial experiment variant
Explain how you would aggregate user data, compute conversion rates, and compare variants. Clarify your handling of missing or incomplete data in the analysis.

3.2.3 The role of A/B testing in measuring the success rate of an analytics experiment
Discuss how you would design an experiment, define success metrics, and ensure statistical validity. Outline your approach to analyzing results and making recommendations.

3.2.4 How would you design and A/B test to confirm a hypothesis?
Describe your process for hypothesis formulation, experiment setup, and result evaluation. Emphasize the importance of randomization and controls.

3.2.5 You work as a data scientist for ride-sharing company. An executive asks how you would evaluate whether a 50% rider discount promotion is a good or bad idea? How would you implement it? What metrics would you track?
Detail your approach to measuring promotion impact, including metrics like incremental revenue, user retention, and cannibalization. Explain how you would design and monitor the experiment.

3.3 Data Engineering & Pipeline Design

Business Intelligence professionals often design robust data pipelines and ensure data quality across diverse sources. These questions test your ability to architect scalable solutions and maintain reliable analytics infrastructure.

3.3.1 Design a scalable ETL pipeline for ingesting heterogeneous data from Skyscanner's partners.
Outline your approach to handling diverse data formats, error handling, and transformation logic. Emphasize scalability and reliability in your solution.

3.3.2 Design an end-to-end data pipeline to process and serve data for predicting bicycle rental volumes.
Describe each stage of the pipeline, from data ingestion to model deployment. Focus on automation, monitoring, and data validation.

3.3.3 Design a data pipeline for hourly user analytics.
Explain your strategy for real-time data collection, aggregation, and reporting. Highlight tools and techniques for managing high-volume, time-series data.

3.3.4 Design a data warehouse for a new online retailer
Discuss your schema design, data modeling, and integration of multiple source systems. Address scalability, query performance, and data governance.

3.3.5 Ensuring data quality within a complex ETL setup
Describe your methods for validating, monitoring, and documenting ETL processes. Emphasize strategies for catching and resolving data inconsistencies.

3.4 SQL & Data Manipulation

Strong SQL skills are essential for extracting, transforming, and analyzing data efficiently. These questions will test your ability to write queries that answer complex business questions and support reporting needs.

3.4.1 Write a query to create a pivot table that shows total sales for each branch by year
Explain how you would use GROUP BY and aggregation functions to summarize sales data. Discuss handling missing values and formatting results for reporting.

3.4.2 Write a SQL query to count transactions filtered by several criterias.
Describe your approach to filtering, joining, and counting records based on multiple conditions. Clarify how you optimize query performance.

3.4.3 Write a SQL query to find the average number of right swipes for different ranking algorithms.
Detail your use of aggregate functions and grouping to compare algorithm performance. Discuss how you would handle outliers or incomplete data.

3.4.4 Write a query to find all users that were at some point "Excited" and have never been "Bored" with a campaign.
Explain how to use conditional aggregation or filtering to identify users meeting both criteria. Highlight your approach for efficiently scanning large event logs.

3.4.5 Write a query to compute cumulative distribution for a dataset
Discuss your use of window functions to calculate running totals or percentiles. Explain the importance of ordering and partitioning the data correctly.

3.5 Behavioral Questions

3.5.1 Tell me about a time you used data to make a decision.
Share a specific example where your analysis led to a concrete business outcome. Focus on your thought process, the impact, and how you communicated results to stakeholders.

3.5.2 Describe a challenging data project and how you handled it.
Highlight the obstacles you faced, your problem-solving approach, and the final resolution. Emphasize teamwork, adaptability, and lessons learned.

3.5.3 How do you handle unclear requirements or ambiguity?
Discuss strategies like stakeholder interviews, iterative prototyping, and regular feedback loops. Show how you clarify goals and deliver value despite uncertainty.

3.5.4 Talk about a time when you had trouble communicating with stakeholders. How were you able to overcome it?
Explain how you identified the communication gap and tailored your approach. Share the outcome and improvements made for future interactions.

3.5.5 Describe a time you had to negotiate scope creep when two departments kept adding “just one more” request. How did you keep the project on track?
Outline how you quantified the additional effort, communicated trade-offs, and used prioritization frameworks. Emphasize protecting data integrity and maintaining trust.

3.5.6 Tell me about a situation where you had to influence stakeholders without formal authority to adopt a data-driven recommendation.
Showcase your ability to build consensus, leverage evidence, and communicate benefits clearly. Highlight the results of your influence.

3.5.7 You’re given a dataset that’s full of duplicates, null values, and inconsistent formatting. The deadline is soon, but leadership wants insights for tomorrow’s decision-making meeting. What do you do?
Describe your triage process, focusing on high-impact cleaning and communicating data limitations transparently. Detail how you balance speed with accuracy.

3.5.8 Give an example of automating recurrent data-quality checks so the same dirty-data crisis doesn’t happen again.
Share the tools, scripts, or processes you implemented. Explain the impact on team efficiency and data reliability.

3.5.9 Tell me about a time you delivered critical insights even though 30% of the dataset had nulls. What analytical trade-offs did you make?
Discuss your approach to handling missing data, the methods chosen, and how you communicated uncertainty. Highlight the business decision enabled by your analysis.

3.5.10 Describe how you prioritized backlog items when multiple executives marked their requests as “high priority.”
Explain your prioritization framework and communication strategy. Emphasize transparency and alignment with business objectives.

4.1 Company-specific tips:

Familiarize yourself with The Rawlings Group’s mission and its focus on healthcare claims recovery. Review how the company pioneered subrogation outsourcing and now specializes in medical claims, mass tort litigation, and pharmaceutical claims recovery. Understand the unique challenges faced by health insurance clients and how data-driven solutions help optimize recovery operations.

Research the business impact of superior financial results in the health insurance industry. Be ready to discuss how business intelligence can support cost recovery, client success, and operational efficiency. Prepare examples that show your understanding of the healthcare landscape and the regulatory environment affecting claims recovery.

Demonstrate your ability to communicate complex data insights to both technical and non-technical stakeholders. The Rawlings Group values clear, actionable reporting—practice translating analytical findings into business recommendations that drive results for clients and internal teams.

4.2 Role-specific tips:

4.2.1 Show proficiency in designing and building dashboards tailored to executive and operational audiences.
Practice creating dashboards that highlight key performance indicators for claims recovery, such as recovery rate, time-to-resolution, and financial impact. Focus on clarity, relevance, and the ability to surface actionable insights for decision-makers.

4.2.2 Be prepared to discuss your experience with data pipeline architecture and ETL workflows.
Review how you have designed robust data pipelines to ingest, transform, and validate data from multiple sources. Emphasize your approach to ensuring data quality, scalability, and reliability, especially in complex healthcare environments.

4.2.3 Demonstrate strong SQL skills for data extraction, manipulation, and reporting.
Practice writing queries that aggregate, filter, and pivot data to answer business questions. Show your ability to handle large datasets, optimize query performance, and deliver accurate results under tight deadlines.

4.2.4 Highlight your ability to make data accessible through effective visualization and storytelling.
Prepare examples of how you’ve used visualization tools to demystify data for non-technical users, choosing the right charts and layouts to communicate trends, anomalies, and opportunities.

4.2.5 Practice translating ambiguous business requirements into analytical solutions.
Be ready to walk through your process for clarifying stakeholder goals, identifying relevant metrics, and iteratively refining your approach. Show how you handle uncertainty and deliver value even when requirements shift.

4.2.6 Prepare to discuss your approach to experimentation and A/B testing.
Review how you’ve designed and interpreted experiments to optimize business processes or product features. Be ready to explain your methodology, metrics selection, and how you ensure statistical validity.

4.2.7 Showcase examples of automating data quality checks and improving data reliability.
Share how you’ve implemented scripts or workflows to catch duplicates, nulls, and formatting inconsistencies before they impact reporting. Emphasize the impact on team efficiency and business decision-making.

4.2.8 Be ready to discuss how you prioritize competing requests and manage stakeholder expectations.
Practice explaining your prioritization framework, balancing business impact, urgency, and resource constraints. Show how you communicate trade-offs and maintain transparency with executives and cross-functional teams.

4.2.9 Demonstrate your ability to deliver insights even when working with incomplete or messy data.
Prepare stories where you extracted meaningful recommendations despite data limitations, clearly outlining the analytical trade-offs and communicating uncertainty to leadership.

4.2.10 Highlight your collaborative approach in cross-functional settings.
Share examples of working with IT, analytics, and business units to ensure data accuracy, resolve misaligned expectations, and drive consensus around data-driven recommendations.

5.1 How hard is the The Rawlings Group Business Intelligence interview?
The Rawlings Group Business Intelligence interview is moderately challenging, especially for candidates without prior healthcare or claims recovery experience. You’ll be tested on your ability to analyze complex datasets, design effective dashboards, and communicate insights to both technical and non-technical stakeholders. The interview also assesses your skills in data pipeline architecture, ETL workflows, and translating ambiguous business requirements into actionable solutions. Candidates who are comfortable with SQL, data visualization, and stakeholder management will find the process rigorous but fair.

5.2 How many interview rounds does The Rawlings Group have for Business Intelligence?
The typical process includes five to six rounds: an initial application and resume review, recruiter screen, technical/case/skills assessment, behavioral interview, final onsite or panel round, and an offer/negotiation stage. Each step is designed to evaluate both your technical expertise and your ability to collaborate and communicate within a fast-paced, data-driven environment.

5.3 Does The Rawlings Group ask for take-home assignments for Business Intelligence?
Yes, many candidates are given a take-home assignment or technical presentation, often involving real-world healthcare data scenarios. These assignments may require you to analyze claims recovery data, build a dashboard, or propose solutions for optimizing data workflows. The goal is to assess your practical skills, attention to detail, and ability to deliver clear, actionable insights.

5.4 What skills are required for the The Rawlings Group Business Intelligence?
Key skills include advanced SQL for data extraction and manipulation, experience with dashboard and report creation, strong data pipeline and ETL workflow design, and the ability to communicate complex findings to non-technical audiences. Familiarity with healthcare data, claims recovery processes, and business metrics is highly valued. Critical thinking, adaptability, and stakeholder management are also essential for success in this role.

5.5 How long does the The Rawlings Group Business Intelligence hiring process take?
The typical hiring process spans 3 to 5 weeks from initial application to offer. Fast-track candidates may progress within 2 to 3 weeks, especially if they have highly relevant experience or internal referrals. Take-home assignments or technical presentations can add several days to the timeline, depending on scheduling and review periods.

5.6 What types of questions are asked in the The Rawlings Group Business Intelligence interview?
Expect a mix of technical, case-based, and behavioral questions. Technical questions cover SQL, data pipeline design, ETL workflows, and dashboard development. Case studies often focus on healthcare claims recovery scenarios, requiring you to analyze data and propose solutions. Behavioral questions assess your ability to manage ambiguity, prioritize competing requests, and communicate insights to diverse stakeholders.

5.7 Does The Rawlings Group give feedback after the Business Intelligence interview?
The Rawlings Group typically provides high-level feedback through recruiters, especially for candidates who reach the final stages. While detailed technical feedback may be limited, you can expect to hear about your overall fit and performance in the interview process.

5.8 What is the acceptance rate for The Rawlings Group Business Intelligence applicants?
While specific acceptance rates are not published, the Business Intelligence role at The Rawlings Group is competitive, with an estimated 3-7% acceptance rate for qualified applicants. The company prioritizes candidates with strong technical skills and relevant healthcare industry experience.

5.9 Does The Rawlings Group hire remote Business Intelligence positions?
The Rawlings Group offers some flexibility for remote work, especially for Business Intelligence roles that support cross-functional teams. However, certain positions may require occasional onsite collaboration or meetings at their headquarters, depending on project needs and team structure. Be sure to clarify remote options during the offer and negotiation stage.

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