Yang (Andy) Yuan Email & Phone Number

• JAD Data is a data engineering team in JR Academy to develop a product recommendation system based on real retail data from Instacart. The project constructs an automated data pipeline based on various AWS services and.
• Collaborated with other two Data Engineers and one DevOps Engineer, and organised daily stand-up and sprint meetings, and monitored progress using Scrum.
• Planed, Configured, Deployed and Operated ETL/ELT pipelines for raw retail data.
• Developed machine learning models for clean retail data.
• Deployed machine learning models to a public web page which served as the recommendation system interface.Achievements:
• Successfully processed the dataset with 3 million customer orders on Instacart by constructing ETL pipelines with various AWS services, such as S3, Redshift, Glue, Athena, Lambda, SNS and EventBridge.

Sydney, New South Wales, Australia

• Suncorp Group is an Australian financial, insurance, and banking conglomerate featuring AAMI, GIO, Suncorp Bank, and Vero among its brands. With more than 9.5 million clients and 13,000 workers, it is a top 50.
• Collaborated with pricing analysts to explore the influences of autonomous technologies in vehicles on claim experience parameters, such as Claim Frequency, Average Claim Size and Cost Per Policy.
• Created data pipelines for processing raw data of claim experience.
• Conducted data analysis and modelling to reveal the underlying drivers of claim differences.
• Proposed recommendations of modifications for the current pricing model of automobile insurance.
• Reported to the senior stakeholders of the results of analysis. Achievements:

Foshan, Guangdong, China

• Country Garden is a property development company based in Guangdong, China. In 2020, it is ranked 147th in Fortune Global 500 List. Country Garden features a market capitalization of over US$29.84 billion as of 2018.
• Developed strategies of land investment in Guangxi Province to support the growth of Country Garden.
• Collected and analysed the data for the investment evaluation reports, economic feasibility studies and risk assessment reports.
• Reported periodically to the senior stakeholders to illustrate recommendations of site or project investments and expected return based on financial analysis. Achievements:
• Successfully purchased 5 projects worth RMB$300 million in Guangxi Province on behalf of the company.
• Successfully created dashboards of land and project information for stakeholders using Excel and Tableau.

Mülheim An Der Ruhr, North Rhine-Westphalia, Germany

• Siemens AG is a German multinational conglomerate with headquarters in Munich and branch offices all over the world. It is Europe's largest industrial manufacturing firm. The Power Diagnostics Center (PDC) is in charge.
• Collected and analysed daily operating data from Siemens gas turbines to track the devices' performance.
• Analysed the alarms generated by GT-AID, a Siemens-developed AI software that monitors and diagnoses faults in gas turbines on a daily basis.
• Investigated and modified those built-in models in GT-AID which always triggered false alarms.
• Cooperated with Software Engineers to update the code in GT-AID, with the goal of reducing false alarms and enhancing forecast accuracy.Achievements:
• Statistically analysed a dataset with 30 thousand records of false alarms using Minitab.

Melbourne, Victoria, Australia

• The Royal Melbourne Institute of Technology or RMIT University, is a public research university in Melbourne, Australia. It focuses on applied research as well as outcome-related research and consultancy services, and.
• Participated in Australian Research Council (ARC) supported project Fundamental Investigation of Heat and Mass Transfer in Nanofluids and conducted theoretical and numerical research.
• Built and programmed numerical models, and conducted numerical simulation of flowing nanofluids.
• Scientifically graphed and analysed simulation data using OriginLab. Achievements:
• Published 6 peer-reviewed journal papers, 5 conference papers.
• Successfully proposed a numerical model and improved the prediction accuracy from 73% to 89% for the simulation of flowing nanofluids.

Master Of Business Analytics, H2A (Distinction)

Key skills: •Programming: Python, R, SQL •Tools: Tableau, R Shiny •Data Warehousing & Big Data: ER Diagram, Star Schema, Dimensional.

Doctor Of Philosophy - Phd, Mechanical Engineering, Computational Fluid Dynamics

Technical skills: Ansys CFX, Fortran Thesis: Numerical modelling of bubbly flows in nanofluids with and without heat transfer.

Bachelor Of Engineering - Be, Energy And Power Engineering, 87/100 (High Distinction)