08/07/2026 updated
100 % available
Data Analyst | Power BI | SQL | Python | Cloud Analytics
melbourne, Australia
Australia
Master of Data ScienceReporting & Visualisation
Expertise in Power BI (DAX, data modelling, dashboard design), Tableau, and Excel (advanced formulas, large datasets) to build executive-level dashboards and reporting streams with zero discrepancy rates.
Data & Cloud Analytics
Proficiency in SQL (querying, joins, validation, extraction) and Alteryx (ETL), with active development of GCP/BigQuery skills to support cloud-native analytics and automated reporting workflows.
Generative AI & Automation
Hands-on Python development using LLM APIs, including building a feedback classification tool for sentiment, theme, and urgency analysis, with practical understanding of prompt design for applied business use cases.
Python Programming
Application of Python for data analysis, scripting, regression and ensemble modelling, and LLM API integration across multiple analytical and automation projects.
ETL Pipeline Development
Design and implementation of ETL pipelines using SQL and Alteryx to transform raw datasets into structured, policy-ready reporting outputs, improving turnaround time by up to 40%.
Data Validation & Quality Assurance
Validation of large datasets at 95%+ accuracy under strict quality benchmarks, supporting AI/LLM model output reliability and maintaining data consistency across reporting pipelines.
Trend & Variance Analysis
Execution of trend, variance, and root-cause analysis alongside KPI tracking, data reconciliation, and requirements gathering to support operational and commercial decision-making.
Stakeholder Communication & Translation
Translation of ad hoc business questions into structured analytical outputs, partnering with cross-functional and policy teams to ensure data-driven decision accuracy.
Expertise in Power BI (DAX, data modelling, dashboard design), Tableau, and Excel (advanced formulas, large datasets) to build executive-level dashboards and reporting streams with zero discrepancy rates.
Data & Cloud Analytics
Proficiency in SQL (querying, joins, validation, extraction) and Alteryx (ETL), with active development of GCP/BigQuery skills to support cloud-native analytics and automated reporting workflows.
Generative AI & Automation
Hands-on Python development using LLM APIs, including building a feedback classification tool for sentiment, theme, and urgency analysis, with practical understanding of prompt design for applied business use cases.
Python Programming
Application of Python for data analysis, scripting, regression and ensemble modelling, and LLM API integration across multiple analytical and automation projects.
ETL Pipeline Development
Design and implementation of ETL pipelines using SQL and Alteryx to transform raw datasets into structured, policy-ready reporting outputs, improving turnaround time by up to 40%.
Data Validation & Quality Assurance
Validation of large datasets at 95%+ accuracy under strict quality benchmarks, supporting AI/LLM model output reliability and maintaining data consistency across reporting pipelines.
Trend & Variance Analysis
Execution of trend, variance, and root-cause analysis alongside KPI tracking, data reconciliation, and requirements gathering to support operational and commercial decision-making.
Stakeholder Communication & Translation
Translation of ad hoc business questions into structured analytical outputs, partnering with cross-functional and policy teams to ensure data-driven decision accuracy.
Experience
Professional experience0 - 5 years
Freelancer since2024
Languages
EnglishNative speaker
Project history
Build and maintain Power BI and Excel dashboards across multiple concurrent project streams for senior leadership, holding a zero discrepancy rate. Write and validate SQL queries to extract, clean, and reconcile datasets. Analyse user activity and engagement patterns for a consumer health and fitness product. Partner with cross-functional teams to translate ad hoc business questions into structured analytical outputs.
Validate large datasets at 95%+ accuracy to support AI model output quality, alongside primary analyst work.
Analysed operational datasets using SQL and Excel to identify cost-saving opportunities and efficiency improvements. Built automated reporting workflows, reducing manual effort by 30-40% and cutting stakeholder turnaround from three days to under 24 hours. Designed structured reporting systems and validation processes to maintain data consistency across pipelines.