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# Principal Data Scientist

- **Company:** Atlassian
- **Location:** San Francisco, CA, United States
- **Salary:** $206,100 - $269,075
- **Contract:** Permanent contract
- **Skills:** Software Quality, Design of User Interfaces, Monitoring of Systems, Human-Computer Interaction, Machine Learning, Feature Engineering, Atlassian Tools, Power Analysis (Cryptography), Data Management
- **Published:** November 4, 2026
- **Apply:** https://www.careerbuilder.com/job-details/principal-data-scientist-san-francisco-ca--b4387272-1c1f-4ad2-af47-2291041a6f71

## About the Role

Data Science, Data Science, Customer Relations, User Interface/Experience (UI/UX), Data Management, Product Strategy, Product Engineering, Analysis Skills, Statistics, Problem Solving Skills

## Description

As a Principal Data Scientist on the Global Experiences Data Science team, you'll sit at the intersection of cutting-edge analytics and Atlassian's most customer-facing products. Reporting to the Manager of Global Experiences Data Science, you'll bring deep technical expertise to complex, ambiguous problems - shaping how millions of users experience Atlassian's suite of products.

This is a high-impact, high-visibility role where you'll lead the full data science lifecycle: from defining the right questions and building robust models to influencing product strategy and communicating insights to senior leaders. You'll be a force multiplier for the team - elevating the craft of data science while partnering closely with Product, Engineering, and Design to drive meaningful outcomes at scale.
Responsibilities:

 * Define and drive the data science strategy for your product area, translating ambiguous business problems into rigorous analytical frameworks and measurable outcomes
 * Lead end-to-end development of ML models and statistical analyses - from problem framing and data acquisition through experimentation, deployment, and ongoing evaluation
 * Partner with Product, Engineering, and Design to embed data-driven decision-making into the product development lifecycle
 * Own experimentation infrastructure and methodology for your domain, including A/B test design, power analysis, and interpretation of results at scale
 * Identify high-impact opportunities through exploratory analysis, surfacing insights that influence roadmap prioritization and business strategy
 * Serve as the technical authority for data science within your team - setting standards for modeling approaches, code quality, and analytical rigor
 * Mentor and develop junior and mid-level data scientists; contribute to hiring, onboarding, and capability-building across the broader DS organization
 * Communicate findings and recommendations clearly to senior stakeholders and executives, translating complex analyses into actionable narratives
 * Collaborate cross-functionally to define metrics frameworks, north star metrics, and guardrail metrics for product and business health
 * Drive adoption of best practices in feature engineering, model monitoring, and responsible AI/ML across teams