Tan Yu Xun

Aspiring data analyst with 5+ years of experience in analysing large datasets, developing statistical models, and providing actionable insights to drive business decisions. Proficient in SQL, Python, and R, with a solid understanding of machine learning algorithms and data visualization techniques. Seeking a challenging and stimulating role in an organization where I can utilize my skills and experience to contribute to its success.

Research and Teaching Assistant Aug 2016 to Oct 2020

Nanyang Technological University

• Designed and implemented survey/interview questions for a large-scale research project on integration.
• Created numerous teaching resources and study materials to facilitate understanding and learning.
• Conducted and facilitated classroom discussions and group activities using interactive platforms such as Kahoot! and Canvas.
• Assisted in the conceptualisation and implementation of student research projects.

Ministry of Education

• Developed and structured specific weekly lesson plans aligned with key educational objectives.
• Planned, organised, and supported school events and activities successfully.
• Designed and developed instructional materials and assessments both independently and collaboratively.
• Evaluated student performance and communicated feedback effectively and concisely to students, parents, and stakeholders.

Rise 2.0 Data Analytics Bootcamp Nov 2022 to Current

Boston Consulting Group

• Built and designed interactive dashboards (Tableau, PowerBI) to generate business insights and support data-driven decision making.
• Completed several exploratory data analysis projects in SQL, informing strategic decision-making by identifying KPIs and trends.
• Analysed and visualized large datasets using Python libraries such as NumPy, Pandas, Matplotlib, Seaborn, Plotly etc.
• Developed and implemented a data-driven predictive model for diabetes progression, using Python, pandas, and scikit-learn for data pre-processing, feature engineering, and machine learning model selection.

International Business Machines (IBM)

• Cleaned and transformed large datasets for exploratory analysis using Python, greatly minimising processing time and improving workflow efficiency.
• Led a team in successfully developing statistical models in predicting heart disease, using regression techniques and machine learning algorithms, achieving a 91% accuracy.
• Helped construct a complaints classifier using Python and NLP techniques such as sentiment analysis, stemming, lemmatisation, TD-IDF etc.