What to expect in the Huawei Data Analyst interview: an HR screen, a technical or hiring-manager conversation about SQL, Python and past projects, and sometimes a final panel or leadership round.
$88K
Avg. Base Comp
$128K
Avg. Total Comp
2-3 rounds
Typical Rounds
Not reported
Process Length
Candidates describe the Huawei Data Analyst interview as practical rather than puzzle-driven. Most start with an HR conversation about background and fit, followed by a technical or hiring-manager round. Across these reports, real project experience matters more than textbook theory.
The technical content varies. One candidate worked through SQL queries, data cleaning and Python analysis, then presented a case study to a panel and was asked how they handled a large dataset. Another was asked about past projects, BI and visualization tools, and how they would apply their skills to Huawei's problems. A third was asked how they would pick a model and define its parameters, with an emphasis on risk and validation. One candidate who was not asked anything technical was surprised by the second round.
Behavioral prep is worth real time. One candidate was asked for a structured, quantified STAR story about a process they improved, and a Junior Data Analyst candidate faced a scenario about a task due by tomorrow morning before a client meeting. Supply chain process questions came up in one report, so ask which team the role supports.
The process is not always smooth. Candidates report rescheduled calls, slow communication and, in one case, a final interview that was postponed and never rescheduled. Keep following up politely and have your project stories ready.
Synthesized from 6 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 Huawei Technologies process.
I applied online and heard back via email pretty quickly. The screening call was supposed to happen, but it got rescheduled multiple times—the interviewer kept having conflicts. When it finally happened, it was a standard video call and felt pretty straightforward, nothing too intense.
Then things got weird. I was told to expect a follow-up email with next steps, but it never came. Instead, on the same day, I got two contradictory messages: a new screening invite and an automated rejection. I reached out to ask for clarification, but nobody responded. The whole thing left me confused about where I actually stood.
The technical prep I did focus on was behavioral storytelling. They specifically wanted me to walk through a project or process I'd improved, using structured, data-oriented outcomes. They were explicit about wanting the STAR method—situation, task, action, result—and they wanted numbers backing up the impact. I also prepped for questions about my work experience in general and what factors would influence my decision between Huawei and other offers. The onsite process, when it did move forward, involved meeting with HR and the supply chain director. HR was personality-focused, while the director dug into my actual process knowledge and experience in the space. Everything was conducted in English.
Prep tip from this candidate
Have a polished STAR story ready with concrete, quantified outcomes for a process or project you improved—they'll ask for it explicitly. Also be prepared for supply chain or operations-specific questions depending on the team, not just general behavioral questions.
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 Huawei Technologies
Lasso vs Ridge
| Question | |
|---|---|
| MLE vs MAP | |
| Your Strengths and Weaknesses | |
| Data Cleaning Experiences | |
| Linear vs Logistic Regression | |
| Backpropagation Explanation | |
| 2nd Highest Salary | |
| Prime to N | |
| Over-Budget Projects | |
| Closed Accounts | |
| Hurdles In Data Projects | |
| Bagging vs Boosting | |
| Size of Joins | |
| Get Top N Frequent Words | |
| Sort Strings | |
| Append Frequency | |
| Find Duplicate Numbers in a List | |
| Random Forest Explanation | |
| Valid Anagram | |
| Xgboost vs Random Forest | |
| Success Measurement | |
| Target Indices | |
| Word Frequency | |
| Check Matching Parentheses | |
| Testing Price Increase | |
| Out of Stock Inventory | |
| Swap Variables | |
| Data Preparation for Imbalanced Data | |
| String Palindromes | |
| Implementing the Fibonacci Sequence in Three Different Methods |
Synthesized from candidate reports. Individual experiences may vary.
Candidates report an initial HR call covering their resume, skills and motivation for the role. One report says English and Mandarin were a plus but not required. In another, the questions were mostly about education and no technical content came up. Expect a conversational fit check.
Candidates report this round varying by team. One worked through SQL, data cleaning and Python analysis. Another discussed past projects and BI or visualization tools. A third talked through model selection and risk controls. It was conversational in the reports that describe the format. Prepare a project you can explain end to end.
Some candidates report a final round with a hiring manager and senior team members, a business unit, or a department head. Reports mention a case study presentation, teamwork and problem-solving questions, and a scenario about a sudden urgent request. It may also include questions on process knowledge, such as supply chain. Not every candidate reported this stage.
Reported outcomes range from offers to no response. Candidates describe slow or sporadic communication, a rescheduled screening call, and one postponed final round that never took place. One candidate described a background check at the end of the process. Plan for possible delays and follow up.
