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Data Assistant

Location:
New Brunswick, New Jersey, United States
Posted:
December 30, 2018

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Resume:

Dai Fang

CELL PHONE: 732-***-****

EMAIL: ac722u@r.postjobfree.com

EDUCATION:

Master of Science in Biostatistics ( 09/2017-expected 06/2019)

Department of Biostatistics, Rutgers University, NJ, USA

Doctor of Medicine(09/2011-06/2016)

Faculty of Medicine, Hubei University of Science and Technology, Xianning, China

Technical SKILLS:

SAS ( SAS certified Advanced Programmer for SAS 9)

R language

Coding

Excel

Photoshop

PowerPoint

MS Word

Language SKILLS:

Native Language

English: TOEFL Score 103; GRE Score 320 (+3.5)

German: studied at Humbold-Gymnasium-Düsseldorf, Germany( 07/2003-05/2005)

EXPERIENCE:

Teaching Assistant:

biostatistics theory I

Department of Biostatistics, Rutgers University

(09/2018-until now)

Assist faculty member with exams, record keeping, and other miscellaneous projects.

Mentor students.

Hand out assignments and grade papers.

Proctor examinations.

Record grades

Summer Intern

Department of Biostatistics, School of Public Health, Yale University

(05/2018-08/2018)

Identified missing data, checked typos, inappropriate unit measurements using conditional statement/ select statement.

Applied data screening criteria, generated clear data screening report, presented results in the form of tables.

Calculated HIV incidence density based on a Poisson distribution, with person-year (PY) over the observed time as the denominator.

Used Chi-square test, multivariate logistic regression model to estimate the factors associated with cohort retention rate and baseline syphilis prevalence.

Project 1: CHD risk factors identification for 4500 simulated patients data by SAS

(10/ 2017 – 11/ 2017)

Sorted and merged different data set

Identified missing data, checked typos, inappropriate unit measurements

Applied data screening criteria, generated clear data screening report for 5 sites

Presented results in the form of tables.

Checked normality/ distribution of data within two CHD groups using proc frequency and univariate analysis.

Applied statistical analysis to identify risk factors for CHD using t-test, Chi-Square test, Wilcoxon Signed Rank Test, Anderson Darling Test, ANOVA, performed data visualization, statistical modeling like logistic regression.

Led in the development of programming process, reviewed and summarized the CHD risk factors analysis reports, and presented results in the form of tables, graphs.

Project 2: Prediction of consumption by SAS

(11/2017 – 12/ 2017)

Prediction of expenditure per year in China by SAS, Adv Regression Meth for PH

Collected data, applied data cleaning, exploratory analysis, such as summary statistics, plots, graphs, univariate analysis, multivariate analysis.

Applied model diagnostic, residual analysis, identified outliers/influential observations/multicollinearity.

Applied model selection, provided model remedies such as Box-cox transformation.

Project 3: Model selection for the Hepatocellular Carcinoma by R

(04/ 2018 – 05/ 2018)

Collected data, applied data cleaning, exploratory analyses, fit cox proportional hazard model.

Applied model diagnostic, residual analysis, identified outliers/influential observations/multicollinearity.

Applied model selection, provided model remedies/transformation for martingale residuals.

Fitted the model, explained the model, and analyzed the risk factors for the Hepatocellular Carcinoma

Research Assistant

Department of Immunology, Tongji Medical College, HUST, China

(07/2016-07/2017)

Cell culture

ELISA

Analyzed data

PUBLICATIONS

1.Qingchun Li, Xiting Li, Yan Luo, Dai Fang, Junfang Chen, Xingliang Zhang, Xin Lv, Jie Jin, Ke Lu, Wenjie Luo, Han-Zhu Qian. HIV incidence and cohort retention among men who have sex with men in Hanzhou, China(under review).

2.Xiangyu Chen, Dai Fang, Lingyun Li, Liyong Chen, Qirui Li, Feili Gong, Min Fang. Glycyrrhizin ameliorates experimental colitis through attenuating interleukin-17-producing T cells responses via regulating on antigen-presenting cells. Immunological Research 2017;65(3):666-680.



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