Hi, I'm Yi Qian

Data and Insights Analyst

Professional data analyst experienced in finance, insurance and customer analytics. Quantitative background in mathematical statistics and machine learning with a focus on turning hard business questions into data-driven answers.

Portrait of Yi

Work Experience

My journey in Data

Data Insights Analyst | Hollard Insurance | Sydney

Feb 2025 - Present

  • Streamlined enterprise-wide reporting suite, reducing the volume of active reports by comparing usage volumes over time. The simplification lessens the workload of the team by more than 100 hours a year.
  • Automated monthly leadership team reporting charts via Power BI and Power Automate, saving approximately 5 analyst-days per month previously spent on manual chart production.
  • Sized the reach of a premium relief initiative for weather-impacted policyholders (capped at 10% premium increases) and quantified the financial impact of weather events on both the broader industry and the firm, through aggregation and transformation of raw claims transactional data.
  • Conducted claims behaviour analysis for vulnerable customers amid the fuel price crisis driven by Middle Eastern geopolitical tensions , supporting member companies in identifying consumers requiring hardship assistance.

Research and Insights Analyst | RACV | Melbourne

Jan 2023 - Jan 2025

  • Analyzed VicRoads data to identify an opportunity to improve campaign trigger dates by 90%. Presented insights and methodology to stakeholders in product and implementation teams, gaining full support and approval.
  • Participated in a firm-wide AI Hackathon leveraging LLMs and NLP to analyze customer call data and identify customer journeys and personas. Proposed actionable solutions, including personalized call responses and building strategic audiences using ML/AI insights.
  • Programmed K-Means Machine Learning algorithm in Python to segment the firm's customer base to a 70-30 split. Customer profiling was performed in Excel to identify the distinguishing features for each cohort. Key analysis and recommendations were suggested to product teams to improve customer acquisitions and product cross-sell.
  • Prepared performance reporting for a new recommendation engine, from data extraction using SQL in Azure Cloud to front-end dashboard build in Tableau. Collaborated with product and analytics teams to scope the project; clarifying reporting assumptions, outputs and timelines. Presented reports and delivered insights to stakeholders across the enterprise.

Education

My background foundations

Graduate Diploma Advanced in Mathematics and Statistics | The University of Melbourne

2022 - 2025

Bachelor of Commerce | The University of Melbourne

2019 - 2022

Certifications

My studies outside work

Skills

My tools and strengths