Resmed Data Scientist interview questions & guide 2026

Our interview process is designed to evaluate your ability to apply data science principles to real-world healthcare challenges. The questions below reflect the patterns we look for, focusing on your technical depth, product intuition, and professional maturity.

Product Sense & Metric Design

These questions test your ability to align data initiatives with user needs and business objectives.

• How would you design a metric to measure the long-term engagement of patients using our connected sleep therapy devices?
• If we observed a sudden drop in user activity metrics, what framework would you use to diagnose the root cause?

Success at Resmed requires a balance of technical precision and strategic thinking. You should prepare not just to provide the "correct" answer, but to demonstrate your thought process and how you navigate trade-offs.

Technical Competency – We expect fluency in SQL, Python, and Machine Learning fundamentals. You will be evaluated on your ability to write clean, efficient code and your depth of knowledge regarding the theoretical underpinnings of your models.

Problem-Solving Ability – You will often face ambiguous scenarios. We assess how you break down these challenges, identify the core constraints, and propose a structured, data-backed approach to finding a solution.

Communication & Influence – As a Data Scientist, your impact is magnified by your ability to persuade others. You must be able to articulate why a specific metric matters or why a certain experimental design is necessary to stakeholders who may not have a technical background.

Leadership & Collaboration – We look for candidates who take ownership of their projects and work effectively within cross-functional teams. Be ready to discuss how you have managed project timelines and contributed to a positive team environment.

The Resmed interview process is structured to give you multiple opportunities to showcase your skills while allowing us to understand your working style. You can expect a mix of technical screens, deep-dive problem solving, and behavioral interviews. We place a high value on candidates who demonstrate a thoughtful, analytical approach to the unique challenges of healthcare data.

This timeline provides a snapshot of the typical progression from initial screening to final assessment. Use this to pace your preparation, ensuring you have dedicated time for both technical drills and reflecting on your professional experiences. Note that individual team requirements may lead to slight variations in the number of rounds.

Data Manipulation & SQL

Proficiency here is a baseline requirement. We evaluate your ability to write complex queries that are performant and readable.

• Window Functions – Essential for time-series analysis and cohort tracking.
• Data Cleaning – Ability to handle nulls, outliers, and duplicates.
• Efficiency – Writing queries that handle large volumes of data without crashing.

As a Data Scientist at Resmed, your primary responsibility is to bridge the gap between raw data and product strategy. You will spend your time mining large datasets to uncover trends in patient therapy usage, designing A/B tests to optimize our digital health platforms, and building machine learning models that help predict patient outcomes.

You will work closely with product managers, software engineers, and clinical teams to ensure that your findings are integrated into the product roadmap. A typical project might involve diagnosing a drop in app retention, proposing an A/B test to improve the onboarding flow, or developing a new metric that better captures user health progress. You are expected to be an advocate for data-driven decision-making throughout the organization.

We are looking for individuals who bring both technical rigor and a passion for healthcare technology.

• Must-have skills:
  • Advanced proficiency in SQL (including window functions and complex joins).
  • Strong command of Python for data manipulation and statistical analysis.
  • Deep understanding of A/B testing methodologies and statistical significance.
  • Proven ability to design product metrics and diagnose performance drops.
• Nice-to-have skills:
  • Experience in the healthcare or medical device industry.
  • Familiarity with cloud-based data warehouses.
  • Experience with machine learning deployment in production environments.

Q: How much time should I spend preparing for the technical rounds? A: Dedicate at least 2–3 weeks of consistent practice. Focus on mastering SQL window functions and reviewing core statistical concepts related to A/B testing.

Q: Is the culture at Resmed collaborative? A: Yes, we highly value cross-functional collaboration. You will work alongside engineers and product managers daily, so demonstrating strong communication skills in behavioral interviews is critical.

Q: What is the typical timeline for the interview process? A: While it varies, most candidates move through the process in 3–5 weeks. We prioritize quality and thoroughness in our assessment.

Q: How can I best prepare for the behavioral portion? A: Use the STAR method (Situation, Task, Action, Result) to structure your answers. Ensure your examples highlight your specific contribution and the impact you had on the outcome.

• Focus on the "Why": In technical questions, don't just provide the answer; explain your reasoning and the trade-offs you considered.
• Master the Basics: Don't overlook foundational statistics. Knowing when to use a specific test is often more important than knowing complex algorithms.
• Understand the Product: Familiarize yourself with the Resmed digital ecosystem. Showing that you understand our users' needs will set you apart.
• Be Concise: When answering behavioral questions, keep your stories focused and structured.

The Data Scientist role at Resmed offers a unique opportunity to apply data science to improve lives at scale. By focusing your preparation on SQL window functions, A/B testing, product metric design, and clear communication, you will be well-positioned to succeed in our interview process. Remember that we are looking for partners who can think critically about data and translate those insights into better product outcomes.

You can explore additional interview insights, practice questions, and preparation resources on Dataford. We encourage you to use these tools to refine your approach and build your confidence.

The compensation data provided above reflects the market range for this position. Candidates should interpret these figures as a starting point, as final offers are determined by a holistic evaluation of your experience, technical expertise, and alignment with the specific needs of the team.