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Atlassian Data Science Team
An inside look at the Atlassian Data Science team — a culture rooted in collaboration, teamwork and psychological safety.
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Employee Reviews
“Authenticity motivated by a common goal goes a long way toward building relationships and getting others invested in collective success. There’s no need to suffer in silence or dance around a challenge — even acknowledging when a solution can’t be implemented immediately creates shared understanding.”
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“I’ve been lucky to work on some great data science teams in the past — but one factor that this team has seemed to ‘get right’ in our distributed working environment is building authentic camaraderie and friendship. No problem is your own to solve, and there are many who are eager to be with you in the thick of it.”
Recently posted jobs
Cloud • Information Technology • Productivity • Security • Software • App development • Automation
Leads complex, cross-functional transformation portfolios across Product, GTM, Strategy, and Operations. Owns program outcomes, operating models, governance, prioritization, dependencies, risks, metrics, and executive communications. Establishes planning frameworks, manages multi-quarter initiatives, aligns stakeholders, and drives measurable business outcomes through structured problem-solving and portfolio execution.
Cloud • Information Technology • Productivity • Security • Software • App development • Automation
Develop and deploy machine learning algorithms and models for Atlassian products. Design model and system architectures, run experiments and evaluations, solve product problems with AI/ML, and contribute to Atlassian Intelligence features. Collaborate with product, engineering, and analytics teams while building scalable, production-quality solutions using large datasets, deep learning, and LLM-related applications.
Cloud • Information Technology • Productivity • Security • Software • App development • Automation
Build and productionize machine learning capabilities for Atlassian’s Feedback product, including retrieval, semantic search, clustering, LLM pipelines, and personalized suggestions. Define evaluation datasets, metrics, experiments, monitoring, and regression checks while balancing quality, latency, cost, and operational complexity. Collaborate with product, design, engineering, and platform teams to turn customer problems into reliable AI features and reusable evaluation tooling.
At a glance
team culture on the data engineering team
Being part of the data engineering team at Atlassian means a few things: centering remote-first communication, letting user feedback guide the project, not being afraid to try new things, and knowing that teammates always have each other’s backs.
