Real, anonymous reports from people who interviewed for Data Scientist at Atlassian, newest first and distilled into what to expect across the loop.
It started with an OA. After that, I had a recruiter screen call, and then the first real technical round was a machine-learning craft style interview where I had to connect system design thinking with details from my own projects. It felt like the interviewer wanted to see how I reason end-to-end, not just whether I could answer trivia.
My process began with a recruiter call, and after that the technical part ended up being fairly straightforward. I only remember getting one SQL question during the technical interview, and then I moved into the behavioral stage. That behavioral portion was split into three interviews total.
The interview process typically begins with a recruiter call followed by an online assessment, which may include coding and SQL questions. Candidates should prepare for a mix of technical skills, including Python and SQL, as well as machine learning concepts.
Candidates can expect a technical interview that often includes SQL questions and case studies focused on metrics and data analysis. The emphasis is on practical application rather than abstract problem-solving, so being able to interpret data and reason through business cases is crucial.
Behavioral rounds are a significant part of the process, often comprising multiple interviews that assess communication skills and alignment with company values. Candidates should be ready to discuss their past experiences and how they approach challenges in a structured manner.
Some interviews include a focus on experimentation, particularly A/B testing, and how candidates think about outcomes. Demonstrating a solid understanding of experimental design and metrics interpretation is beneficial.
The overall difficulty of the interview process is generally perceived as average, with a structured flow that emphasizes consistency across interviews. Candidates may find the pacing steady but should be prepared for a potentially lengthy timeline between rounds.
Candidates noted that while feedback was often informative, the lack of clarity regarding fit for specific roles and the lengthy process could be draining. It's important to seek clarity on the role being considered throughout the process.