Philips Data Analyst interviews, as candidates describe them, mix conversational screens, practical Power BI and Excel questions, and in one report SQL and sorting coding questions. Includes process steps and prep tips.
$93K
Avg. Base Comp
$105K
Avg. Total Comp
Not reported
Typical Rounds
Not reported
Process Length
Philips candidate reports differ by track, so prepare for more than one format. One Data Analyst candidate described an AI-powered first round on communication and situational judgment, then a job-related technical assessment, a coding round with three LeetCode-style questions, more technical interviews and an HR round. The questions touched SQL joins and sorting, and one interviewer asked for ideas on data management innovations in healthcare.
Another candidate, who received an offer for an analyst role, described several 30-minute conversations with HR and the analytics team. HR asked about future and salary expectations, and the team asked about past projects and whether the candidate had used Power BI and Excel. The tone was collaborative rather than adversarial.
A Data Analyst Intern report began differently: an online assessment mixing typed and video answers in Spanish or English, plus timed games including a numerical operations exercise. An HR interview followed, covering why the candidate wanted to be a data analyst, the analysis process from start to finish, how to approach a business problem, and the biggest challenge faced and how it was handled.
To prepare, refresh SQL joins and sorting, be ready to walk through Power BI and Excel work from past projects, and bring a real challenge example with the specific steps you took. Have a considered answer on salary and career expectations too, since HR asked directly in one report.
Synthesized from 4 candidate reports by our editorial team.
Had an interview recently?
Share your experience. Unlock the full guide.
Real interview reports from people who went through the Philips process.
I interviewed at Philips for a Data Analyst role, and the process felt pretty laid-back overall. The interview was structured around several thirty-minute rounds with both HR and members of the analytics team I'd be joining. In the first round, HR asked about my future expectations and salary expectations — pretty standard fit questions to gauge alignment. What stood out was how comfortable the conversation felt; they weren't trying to trick me or throw curveballs.
When I met with the team, they were genuinely interested in my background. We spent time talking through projects I'd worked on at my previous company and how my experience could add value to their team. They asked about my technical skills, specifically whether I'd worked with Power BI and how comfortable I was with Excel. These weren't gotcha questions — they were assessing whether I had the practical tools they needed. The whole vibe was collaborative rather than adversarial, which made it easy to talk through my work and think out loud about how I'd approach problems.
The main takeaway was that Philips seemed to value culture fit and practical experience over drilling you on edge cases or theoretical concepts. They wanted to understand how you'd actually work and contribute, not just whether you could solve an abstract problem under pressure. By the end, I felt like I had a realistic sense of the role and the team, and they seemed to have a good sense of whether I'd be a good fit.
Prep tip from this candidate
Come ready to discuss specific projects from your previous role and demonstrate hands-on experience with Power BI and Excel — the team cares more about practical capability than algorithmic problem-solving. Avoid vague responses to fit questions about salary and career expectations; they ask directly, so have thoughtful answers ready.
Share your own interview experience to unlock all reports, or subscribe for full access.
Sourced from candidate reports and verified by our team.
Topics based on recent interview experiences.
Featured question at Philips
Describing a data project and its challenges
| Question | |
|---|---|
| Overfit Avoidance | |
| Decision Tree Evaluation | |
| Alternative Vendor Tradeoff | |
| Client Solution Pushback | |
| Why Do You Want to Work With Us | |
| Your Strengths and Weaknesses | |
| Empty Neighborhoods | |
| 2nd Highest Salary | |
| Experiment Validity | |
| Prime to N | |
| Button AB Test | |
| Rain in N Days | |
| Random SQL Sample | |
| Last Transaction | |
| P-value to a Layman | |
| Size of Joins | |
| Paired Products | |
| Upsell Transactions | |
| Total Spent on Products | |
| Bagging vs Boosting | |
| Find the Missing Number | |
| Detecting ECG Tachycardia Runs | |
| Cumulative Distribution | |
| Brain Cancer Treatment Outcomes | |
| Fair Coin | |
| Exam Scores | |
| Random Forest Explanation | |
| Valid Anagram | |
| Google Maps Improvement |
Synthesized from candidate reports. Individual experiences may vary.
Candidates report different openings. One Data Analyst candidate described an AI-powered conversational round on communication and situational judgment. An intern candidate reported an online assessment with typed and video answers plus timed numerical games. Another analyst candidate began with an HR conversation about expectations.
One Data Analyst candidate described a job-related technical assessment that felt manageable. The other reports did not mention this step, so it may not apply to every analyst track and should be treated as one candidate's experience.
The same candidate reported three LeetCode-style questions ranging from medium to hard, covering SQL joins and sorting. The candidate felt the focus was on core foundations rather than exotic algorithms. The other analyst reports did not describe this round, so treat it as a possibility rather than a certainty.
An analyst candidate who received an offer described roughly 30-minute conversations with analytics team members about past projects and comfort with Power BI and Excel. A different candidate reported technical interviews with several interviewers, including a question about data management innovation in healthcare.
In one report, HR asked directly about future expectations and salary expectations. An intern candidate described an HR interview on why they wanted to be a data analyst, the analysis process from start to finish, how they approach a business problem, and their biggest challenge and how they handled it.
