Jiaxin Cheng
Sydney,NSW
Overview
2
2
years of professional experience
Work History
Intern
Nanjing Planning And Natural Resources Bureau
09.2021 - 01.2022
- I extensively explored various smart city projects.
- I learned traffic data collection and processing, using sensors and cameras.
- I was responsible for data cleaning, preprocessing, and applying machine learning for analysis.
- I also participated in a smart environmental monitoring initiative.
- I collected and processed real-time data using sensors. Collaborating, we explored environmental protection solutions.
- Finally, I also helped team develop community app, interfacing with databases for information retrieval.
Intern
China Securities Co., Ltd Jiangsu Branch
07.2020 - 09.2020
- Involved in studying national financial laws, regulations and corporate financial products, understood the specific operation procedures of the relevant product evaluation, review, and approval procedures.
- Assisted Product Department colleagues in sorting out company's product system, including the data sorting and summary of cash management, fixed income, public offering, private equity and other products.
- Studied the various products elements, investment direction, risk levels, customer types and securities industry developing trends.
Education
Master of Science - Information Technology
University of Queensland
Brisbane, QLD12.2023
Bachelor of Science - Economics
University of Toronto
Toronto11.2021
Skills
- Data Analysis/Business Analytics with Excel/Python/R
- Web Development: HTML/CSS/Nodejs/JavaScript/React
- Java/R/Python
- MongoDB/MySQL/Tableau
- PowerPoint/Excel
- Machine Learning and Data Mining
- IELTS: 7
Projects
- Predicted the Result and Analyzed the Overall Popular Vote of the 2020 American Federal Election Using a Regression Model with Post-stratification (10/2020 - 11/2020)
- Instructed by Samantha-Jo Caetano
- Built the linear regression model on the sample data and did the analysis. Elaborated on the results and make prediction. Addressed weakness of the analysis and future steps of the analysis.
- Successfully predicting the results of the 2020 American federal election.
- Built an Appropriate Model to Analyze the Data Set from General Social Survey on Family (cycle 31), 2017 for the Relationship between Income, the Age of First Marriage, and the age of Having the First Child. (09/2020 - 10/2020)
- Instructed by Samantha-Jo
- Built the Multiple linear regression model, fitted the data into an MLR and got the relevant findings, and then did discussions based on the results, to see how the results contribute to the goal of study.
- Findings from the result sections demonstrate that age at first marriage and family income indeed were factors that contributing to the age of people when having their first child; Older age at first marriage and higher family income generally lead to an older age at first birth.
- Predicting Whether it will Rain Tomorrow by Logistic Model (07/2020 - 08/2020)
- Instructed by George Stefan
- Made decision whether to fit the GLMM and GLM model and explain the assumptions to fit a GLM and GLMM model which assumes independence. Properly explained in detail how I choose the modelling technique.
- Properly chose the variables based on Akaike information criterion and Bayesian information criterion for inclusion in the model and explain the reason.
- Presented the Numerical/Visual summaries of the important variables and explained important features.
- Validated the final model correctly, verified the model assumptions and performed the appropriate model diagnostics and finally interpreted the final model in context.
- The model was able to effectively predict the short term weather.
Timeline
Intern
Nanjing Planning And Natural Resources Bureau
09.2021 - 01.2022
Intern
China Securities Co., Ltd Jiangsu Branch
07.2020 - 09.2020
Master of Science - Information Technology
University of Queensland
Bachelor of Science - Economics
University of Toronto
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