Principal Data Scientist

Analytics & Data Science | Bengaluru, India | Remote, Remote | Remote, India



Overview

Does the challenge of scaling a fast-growing company with the latest in data science and AI methodologies and tooling excite you?

Using your business instincts and creativity, you will leverage your business, data science, analytics and AI acumen to support a highly strategic, mission-critical initiative for Service Collection. This role aims to leverage analytics, data science and AI/ML to identify opportunities, build tools and solutions that will influence our Service Collection roadmap. If you love blazing new innovative trails, making the complex simple and driving decision-making speed across business units with data insights, then read on!

• Influence strategy & important decisions around Service Collection by blending end-to-end business acumen with advanced data science methodologies
• Define, set and report on department level KRs to the Service Collection R&D team
• Build and implement measurement frameworks, machine learning models and other tooling leveraging various data science methods to accelerate Atlassian's growth and influence our product roadmap.
• Envision, scope, and lead high impact projects by collaborating with Engineering, Product Management and Design, Data Engineering and Research and Insights teams.
• Foster a world-class Data Science culture by leading training on technical concepts, driving continuous learning and mentoring Data Scientists on the team

• Experience applying your Data Science skills to identify and lead projects which have had impact on business strategy and performance
• 9+ years of experience in Data Science or related fields. (Preferred - 10+ years experience with a post-graduate degree in a quantitative discipline like Statistics, Mathematics, Econometrics, Computer science)
• Expertise in applying a broad variety of ML methods including LLM to solve business problems and a strong sense of when to apply them to the problem at hand
• Expertise in SQL and in another data science programming language (e.g Python, R) with expertise in libraries like Pandas, Numpy, Scikit-learn etc.
• A very high bar for output quality, while balancing "having something now" vs. "perfection in the future"
• Comfort explaining complex concepts to diverse audiences and creating compelling stories for non-data experts
• Proficiency in visualization tools (e.g. Streamlit, Tableau, R-shiny) and libraries (e.g. - matplotlib, bokeh)