Lan Zhang Email & Phone Number

New York, Ny, Us

New York, New York, United States

• Investigated in 9 US statewide educational databases including over 50,000,000 data entries and 2,000 variables with K-means clustering and KNN in R to map k-12 school equity indicators to public urban school districts • Employed PCA, t-SNE, and UMAP for high dimensional data visualization to identify data pattern and outlier schools that need additional support; utilized ComplexHeatmap and tmap to generate hierarchical cluster heatmap and thematic maps to visualize data mining outcomes, offer deep perceptivity and data awareness for district directors• Collaborated with team members to manage large dataset to ensure data accuracy and completeness; utilized SQL and ETL tools to extract, transform, and load data from multiple sources into centralize database; assisted in composing conference abstract for presentation and reporting

New York, New York, United States

• Conducted Multilevel Linear Regression, Multivariate Analysis, and Random Forest on departmental budget data through Python to discern data impact factors; created data visualizations via Seaborn and composed over 5 financial reports for senior managers to offer fresh ideas for better administration and interdepartmental collaboration • Explored over 3,000,000 rows of the fundraising data and implemented data cleaning using Python; applied K-means clustering to find potential clients and funders, did hyperparameter tuning resulting 27% increase in model accuracy; wrote queries through MySQL to map and analyze over 4 large databases; developed 6 dashboards using Power BI to present business intelligence and management insights for department head

Wuhan, Hubei, China

• Collected daily stock price of oil, finance and real estate industries, applied pivot table in Excel filtered top 10 stocks in each industry, visualized the properties of stocks in Tableau and reported to supervisor, deepened team’s risk knowledge in market• Utilized Scikit-learn and Matplotlib in Python to analyze and visualize price data, built and trained model via Naïve Bayes and K-means to predict top stocks, successfully forecasted over 20 stocks and earned over $50,000 for 6 customers in 2-month period• To predict future tendency in China’s social media industry, analyzed historical stock data via SVM and composed 30 pages report, increasing industry understanding for team and convinced more than 10 customers to invest based on report presentation

Rochester, New York, United States

• Conducted analysis in large administrative & clinical inpatient, emergency, and outpatient databases using STATA and R to investigate factors & results in patients undergoing cranial neurosurgery procedures with early Do-Not-Resuscitate Orders (DNR)• Programmed for applications of advanced analyzing techniques; created literature supplemental materials including survival analysis table with hazard ratio and flow chart of data selection• Contributed to research results showcased at the Neurocritical Care Society 20th annual meeting• Assisted in composing literature accepted by Journal of Clinical NeuroscienceZhang, L., Albert, G., et al. (2023). Association of Do-Not-Resuscitate Orders and In-hospital Mortality Among PatientsUndergoing Cranial Neurosurgery. Journal of Clinical Neuroscience, vol.118, December 2023, pp.26-33. DOI: 10.1016/j.jocn.2023.10.006

Rochester, New York, United States

• Programmed a R software framework to make out-of-sample predictions of cell subpopulation from single cell RNAseq data; resulting more robust and reproducible cluster assignments on cells• Conducted numerical experiments to characterize the behavior of this framework on four distinct datasets, totaling more than 10,000,000 cells• Showcased these research results at the Upstate New York Statistics Conference 2022 and University of Rochester Medical Center 2022 Genetics Day reaching 150 people

Rochester, New York, United States

• One-on-one tutored over 30 students to help them prepare for exams and projects, study and comprehend weekly assignments, and develop new learnings in Intermediate Calculus, Multidimensional Calculus, and Applied Statistics• Explained mathematical and statistical concepts such as differentiation, integration, Poisson process, and Chi-Square test; guided students to think through specific problems by asking interactive questions, helping tutees improve learning abilities

Rochester, New York, United States

• Organized workshops for 25 students to review weekly materials for Introductory and Intermediate Calculus courses • Led discussions on resolving after-class practice problems, and assisted students through email to solve mathematical problems at an average rate of 50 emails per week

Wuhan, Hubei, China

• Assisted in fixing and patching the backstage issues of Hubei Bank mobile app and website, developing the app productivity from supporting 8,000 people/day to over 15,000 people/day• Tested the accessibility of the mobile app, experienced the functions of app and proposed suggestions for optimization, improving the designation of UI and customers’ experience• Monitored the number of daily active users (DAU) and their active time period at mobile app, fitted linear regression models using Excel and Python, wrote weekly summary to report user patterns; helped organizing activities in attracting more than 1,000 customers based on popular time slots predicted by models

Master Of Science - Ms, Applied Statistics

Bachelor Of Science - Bs, Business Analytics

Bachelor Of Arts - Ba, Statistics