Melbourne, Victoria, Australia
As a data-driven professional with over 2+ years of experience and a proactive, adaptable approach, I am eager to join a collaborative environment where I can apply my expertise in machine learning, data visualization, and reporting to drive organizational success. I learn quickly and thrive when tackling new challenges. Balancing independence with teamwork, I am confident in my ability to deliver impactful insights and add value in a data-focused role.
• Delivered end-to-end fraud and security analytics using Power BI, SQL, Excel, and Snowflake, transforming manual reporting into automated dashboards, and reducing reporting turnaround time by 60% • Replaced manual offender analysis with centralized Power BI dashboards, improving investigation efficiency by 90% and enabling faster identification of repeat offenders and trends. • Developed advanced DAX measures, calculated columns, and KPI frameworks to track total loss, recovered and unrecovered value, and offender behavior patterns. • Integrated and modeled large-scale incident data from Snowflake, building interactive and geospatial dashboards to identify high-risk hotspots and support data-driven loss prevention strategies.
• Enhanced motor vehicle fraud detection accuracy through data standardization and real-time alert systems, improving accuracy by 15%. • Analyzed and managed extensive financial and insurance data to identify fraud trends and streamline claims processing. • Developed and maintained Power BI dashboards for claims and fraud analysis, cutting case resolution times by over 50%. • Collaborated with cross-functional teams to integrate analytical outputs into existing workflows effectively.
• Audited and optimized user access permissions, reducing over-permissioning risks by 30%. • Developed T-SQL scripts for transforming raw access data into actionable reports. • Automated SQL reports with Excel integration, enhancing discrepancy detection by 40%. • Designed standardized RBAC frameworks, decreasing manual access management by 25%.
• Enhanced motor vehicle fraud detection accuracy through data standardization and real-time alert systems, improving accuracy by 15%. • Analyzed high volumes of financial and insurance data to identify fraud trends and optimize claims processing. • Developed Power BI dashboards, reducing case resolution times by over 50%. • Collaborated with cross-functional teams to integrate analytical outputs into existing workflows.
• Led a team project to develop predictive models for racehorse performance using machine learning techniques. • Achieved 94% accuracy with an interactive bagging model, surpassing other methodologies. • Executed data pre-processing, feature selection, and model tuning to provide actionable insights. • Utilized Python and Power BI for data visualizations, enhancing reporting capabilities for stakeholders at Ciaron Maher Racing.
• Achieved customer activity KPIs by enhancing data validation for vulnerable customer segments. • Developed interactive dashboards and data visualizations using Tableau for effective stakeholder communication. • Streamlined data flows and improved reporting accuracy through Microsoft Synapse for data modeling and ETL processes.
• Developed a Semantic Layer on the Dremio Platform to implement business rules effectively. • Collaborated with stakeholders to ensure seamless integration of data processes. • Enhanced data modeling and querying capabilities using Microsoft SQL. • Executed data backtracking from Dremio to Microsoft Azure for efficient data transfer.