Senior Data Scientist, Finance

Xero

Senior Data Scientist in Finance designing models and analytics for decision-making. Collaborating with teams to provide effective data solutions and insights for organizational growth.

Posted 7/24/2026full-timeMelbourne • 🇦🇺 AustraliaSeniorWebsite

Core Competencies

Role fit

Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates expertise in SQL and Python or R for data analysis and model deployment, with a strong foundation in statistical and machine learning techniques. Capable of mentoring teams and translating complex data into actionable insights for Finance and G&A functions.

Highest-signal resume keywords

SQL Data ExtractionPython Data Science WorkflowStatistical AnalysisMachine Learning TechniquesData Visualization with Tableau

ATS Keywords

Tailor your resume

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills

SQLPythonRStatistical TechniquesMachine LearningTime-Series ForecastingRegression AnalysisClassificationCausal InferenceFeature Engineering

Soft Skills

Problem-FramingMentoringCollaboration

Tools & Technologies

Tableau

Industry Keywords

FinanceG&AData ScienceAnalyticsPerformance Management

Tech Stack

Tools & technologies

PythonSQLTableau

About the role

Key responsibilities & impact

Design and deliver models, analytics, and insight frameworks for faster decision-making within Finance and G&A teams
Lead forecasting, planning, and performance management efforts, embedding models in key operational cycles
Build solutions independently as part of a high-impact team
Mentor analysts and data scientists across G&A to enhance AI and advanced analytics application
Collaborate with teams to create usable models and dashboards from complex data

Requirements

What you’ll need

Strong SQL skills for extracting, wrangling, and analyzing large, complex datasets
Solid Python or R experience across the full data science workflow, from feature engineering to model deployment
Good grounding in statistical and machine learning techniques, including time-series forecasting, regression, classification, and causal inference
Comfortable with data visualisation tools like Tableau to communicate complex analysis to non-technical stakeholders
Strong problem-framing skills to translate ambiguous business questions into clear analytical problems
Experience partnering with Finance or a similar corporate function

Benefits

Comp & perks

Hybrid work model combining in-office collaboration with remote work flexibility
Mentoring opportunities
Professional development and growth within the team