statistical programmer/data analyst
Biostatistics
Location: Highland Park, NJ, United States
School: Rutgers University-New Brunswick
Field of Study: Biostatistics

statistical programmer/data analyst

Yuanyuan Qiu


PROFESSIONAL SUMMARY


A recent Master of Science in Biostatistics graduate from Rutgers University School of Public Health seeking to obtain a position as a statistical SAS programmer or data analyst. A Certified Base and Advanced SAS Programmer for SAS 9 with excellent expertise in basic SAS procedures and in-depth knowledge of data analysis and statistical modeling. Additional one-year experience working in a pharmaceutical research lab and thus proficient in biological and pharmaceutical lab techniques. A permanent resident who is authorized to work in the United States.

SKILLS and CERTIFICTION

• Certified Base and Advanced SAS programmer for SAS 9
• Excellent SAS/R programming skills and solid knowledge of data analysis and statistical modeling
• Experience utilizing SAS procedures for data extraction, cleaning, loading, and reporting
• Knowledge of drop, keep, retain, formats, date manipulations, generating reports, and listings and graphs using SAS
• Knowledge of macros and SQL in SAS
• Knowledge of FDA submission procedure and CDISC standards including SDTM and ADaM
• Excellent communication skills both oral and written, ability to relate relevant information to appropriate personnel, and ability to work in teams and in challenging environments
• Highly effective assessment, analytical, and organizational skills, adept at managing multiple tasks and resolving problems
EDUCATION

Rutgers University School of Public Health–New Brunswick Piscataway, NJ
M.S. in Biostatistics GPA: 3.72/4.0 May 2017
Relevant coursework: Clinical Trials, Advanced Regression Methods, Survival Analysis, Biostatistics Theory I & II, Principles and Methods of Epidemiology, Biometrics Computing

University of Wisconsin–Madison Madison, WI B.S. in Biology May 2015
EXPERIENCE

Research Assistant, Dr. Lingjun Li Lab, School of Pharmacy, University of Wisconsin-Madison Madison, WI
Jan. 2012 – Dec. 2012
Project: Comparison of Proteomic Profiles of Leukemic and Primary Natural Killer Cells using Mass Spectrometry
Mentor: Di Ma (PhD)
Project: Mapping of Neuropeptides in the Crustacean Stomatogastric Nervous System (STNS) by Imaging Mass Spectrometry
Mentor: Vivian Hui Ye (PhD)
• Comparative neuropeptide study: applied large-scale proteomic techniques to neurons of mice for disease diagnosis and biomarker discovery
• Prepared samples, designed methods, collected data, and interpreted results using ion mobility-mass spectrometry
• Determined the relative protein amount via the method of isobaric tags for relative and absolute quantification (iTRAQ)
• Collected results from the mass spectrum based on relative abundance of fragments and sorted results using Microsoft Excel
Volunteer Digestive Health Unit, Meriter Hospital Madison, WI
Sept. 2012 – Nov. 2012
• Conducted surveys and questionnaires for research purposes with patients
• Served as a nursing assistant and receptionist in Digestive Health Unit

Yuanyuan Qiu




Volunteer Smoking Cessation Program, Meriter Hospital Madison, WI
• Helped patients quit smoking by suggesting electronic cigarettes, nicotine inhalers, and patches Mar. 2012 – May 2012
• Facilitated interactive discussions with smokers
• Organized and sorted demographic profiles of smoking patients
• Conducted follow-up phone calls to participants in the smoking cessation program

OTHER PROJECTS


Master of Science Thesis Project Jan. 2017 – May 2017
Mentor: Dr. Yong Lin
• Summarized and analyzed the article Optimal Allocation of Participants for the Estimation of Selection, Preference and Treatment Effects in the Two-stage Randomized Trial Design by Walter, S. D.
• Optimized allocation of participants based on estimated treatment, selection and preference effect
• Conceived codes to regenerate tables and figures using R and Microsoft Word
• Detailed derivations and calculations of formulas and equations for optimization of two-stage randomized design
• Expanded unexplained ideas and compared similar approaches to find optimal allocation of participants
• Established assumptions based on equivalent variances of between and within group

Categorical Analysis on Conditional Association between Age and Aftercare Placement Result for Patients with Psychiatric Disorders
Nov. 2016 – Dec. 2016
• Tested conditional association between age and aftercare placement result
• Determined whether age modifies effect of behavioral symptoms score on aftercare placement result
• Generated SAS programs using PROC IMPORT, PROC FREQ, PROC SORT, and PROC LOGISTIC
• Conducted non-statistical and statistical analyses such as bivariate and multivariate analyses by logistic regression using SAS 9.4

Linear Regression Modeling on Total Cholesterol Level for Men with Age Below 50 Nov. 2015 – Dec. 2015
• Prepared new datasets from raw data files using import techniques and modified existing datasets using data steps, set, merge, sort, and formats using SAS 9.4
• Conducted linear regression model selection to determine significant risk factors using SAS 9.4
• Developed SAS programs including PROC REG, PROC UNIVARIATE, PROC MEANS, and PROC SGSCATTER
• Performed statistical analysis consisting of exploratory analysis, univariate analysis, multivariate analysis, model assumption and multicollinearity determination, outlier/high leverage/influential observations check, and model transformation
• Selected significant predictors that have linear association with outcome variable

OTHER SKILLS

• Computer: Expert in Microsoft Office (Word, Excel, PowerPoint), statistical data management software (SAS, R, SPSS), and computational chemistry software WebMO
• Language: Fluent in Mandarin Chinese and English
• Lab experience with high-performance liquid chromatography (HPLC) and nuclear magnetic resonance (NMR)/mass spectrometry
• Preparing biological samples, such as blood, food, and bacteria cultures, for routine testing and laboratory analysis
• Lab skills such as cell culturing and polymerase chain reaction (PCR) analysis