Senior Data Scientist, Finance - xero

THE ROLE

& IMPACT

As a Senior Data Scientist in the Finance G&A Data & Analytics team, you'll design and deliver the models, analytics and insight frameworks that help Xero's Finance and Corporate (G&A) teams make faster, better decisions. You'll lead work on forecasting, planning and performance management, embedding your models directly into core rhythms like Central dashboards, MBR and QBR cycles, and you'll act as a senior partner to G&A leaders, helping them frame problems and use data to balance growth, profitability, risk and people outcomes.

This is a hands-on role in a small, high-impact team. You'll build solutions yourself rather than just directing others to build them, while also mentoring analysts and data scientists across G&A and helping shape how Xero applies AI and advanced analytics in an increasingly self-serve, agent-first environment.

Your work will directly influence how G&A leaders plan, measure performance and make investment decisions.

THE TEAM & HOW THEY CONNECT

The Finance G&A Data & Analytics team exists to give Xeros across Finance, People Experience and other G&A functions trusted data, analytics and AI-driven insight. It's a small team that works closely with Finance, Data & Analytics Engineering, and Insights, Analytics & Reporting colleagues to turn complex data into models and dashboards people actually use.

You'll also connect with GTM and Product data teams to keep shared metrics and definitions consistent across Xero. Our current stack includes SQL, Python (or R) and Tableau, alongside modern data tooling such as Snowflake, dbt and Airflow.

INITIALLY, YOU WILL FOCUS ON

• Revenue and cost forecasting, plus scenario analysis linked to GTM and Product data.
• Operating expense optimisation across areas like vendor, cloud, travel and property spend.
• Looking ahead, maturing Xero's functional data model for G&A, including how AI and advanced analytics show up in an agent-first, self-serve environment.

WHERE AND HOW YOU CAN WORK

This role can be based in Melbourne or Sydney, working in a hybrid model that combines in office collaboration with the flexibility to work from home. Our boost days bring the team together in person for connection and collaborative work, with the rest of the week flexible to suit how you work best.

HERE ARE SOME OF THE THINGS WE'RE LOOKING FOR, FOR THIS ROLE

• You'll bring strong SQL skills and feel comfortable extracting, wrangling and analysing large, complex datasets.
• Solid Python or R experience across the full data science workflow, from data wrangling and feature engineering through to model deployment.
• A good grounding in statistical and machine learning techniques, including time-series forecasting, regression, classification and causal inference.