Programmer Analyst
Resume:
Yafen Huang
*****.*****@*****.***
Proactive, independent and disciplined team player who thrives in the fast, dynamic and cross-functional team environment; Strategic planner, analytical thinker and problem solver who has exceptional attention to details; Excellent communication and facilitation skills to connect with cross-disciplinary professionals; Strong desire to know why and commitment to self-development and expanding knowledge base
3+ experience in data management, programming and analytics
Broad knowledge and experience in statistics, biomedical, clinical research design and protocol development
Knowledge and understanding of CDISC standards (SDTM, ADaM), GCP, ICH, FDA regulatory guidelines
Strong analytic thinking to understand project goals and break them down into strategic analytic framework and working plan
Experience in translating business process into data modeling, schema design and object implementation
Extensive experience in Base SAS data step programming, using SET, MERGE, IMPORT, ARRAY, FORMAT, SORT, TRANSPOSE for importing, extracting and transforming data
Expertise in creating SAS/SQL join, sub-query, in line view to extract data in complex contexts
Skill in exploring, summarizing and reporting data with SAS/MEANS, FREQ,UNIVARIATE, SGPLOT, REPORT, TABULATE and ODS
Proficiency in automating data manipulation and reporting process by implementing SAS/MACROS, SQL stored procedures, user defined functions, triggers and dynamic SQL
Skilled in statistical method selection, using SAS/TTEST, ANNOVA, CORR, REG for hypothesis testing, model development and tuning to deliver better and informed solution
Experience in performance tuning by optimizing object structure and data step programming
Experience in database administration including managing metadata, ensuring data security, database backup and recovery
Good practice in standardizing operational procedures, tracking and managing status updates and business documentations
Excellent communication skills to stimulate insights from professionals with different backgrounds and ensure alignment between expectations and outcomes
Strong problem-solving skills in troubleshooting and performance tuning
Prioritized tasks and meet deadline always based on the level of importance and urgency for the projects Programming Languages: SAS, SQL, Python, R, C#
Analytic Tools: SAS (v9.x), Jupyter Notebook, Tableau, SSRS, SSIS, Crystal Report Writing Skills: Medical, scientific and business writing Management Tools: Microsoft Office, Visio
SAS Certified Advanced Programmer for SAS 9
SAS Certified Base Programmer for SAS 9
Ph.D. of Biomedical Science Nanyang Technological University, Singapore PROFESSIONAL SUMMARY
EDUCATION
SKILLS
CERTIFICATION
Programmer Analyst
Measurement INC (Durham, NC) 2015-present
The company provides national wide educational assessment service to government agencies and educational institutions. As a technical lead, I am responsible for collaborating with project team in managing data manipulation, validation and reporting in both efficient and effective manner Responsibilities
Organized and facilitated brainstorming, interviewing sessions to gather data requirements from subject matter experts and end user
Performed GAP analysis to configure the “As is” and “To be” states and identified opportunities to close gap
Developed database physical design and used SQL DDL for creating tables, clustered/non-clustered indexes and constraints
Designed data flow for integrating data from a variety of sources including flat, excel, XML and JSON
Developed SAS Macros for automating data loading, transforming and generating statistical summary report
Optimized query structure and performance for dataset with large volume and velocity
Designed and implemented dynamic SQL, nested store procedures to enhance process efficacy and data accuracy for data transfer across multiple functional databases
Developed scheduled procedures for automating data tracking and quality check on daily basis, and optimized the object structure to be flexible and adaptable across different projects
Applied SAS/MEANS, UNIVARIATE, FREQ, SGPLPOT for visualizing the distribution and trending of data and identified outliers that require further investigation
Used SAS/ODS, TABULATE, REPORT for creating ad-hoc report, facilitating communication across different functional domains
Tracked, managed and communicated status updates to project managers in a timely manner
Identified issues, evaluated their impacts on processes with dependence and initiated action plans efficiently and effectively
Documented business logic, procedures, issues and solutions regularly for future reference and clarity Data Curation Scientist (Part time weekend)
OmicSoft Qiagen (Durham, NC) 2017-present
OmicSoft focuses on biomarker data management, visualization and analysis. The aim of the project is to develop software that integrate analysis of next generation sequencing, bioinformatics, cancer genomics and laboratory findings so that not only it is easy enough to be used by the bench scientist, but also powerful enough to be used by the bioinformatician or statistician
Responsibilities
Reviewed the scientific publications, protocols to evaluate study aims, design, methods and research findings in cancer research and clinical trial studies
Coordinated the genomic data curation team to extract, organize biological/clinical project and sample meta- data from various sources
Standardized and annotated various kinds of patient demographic, diagnosis, pathology features, biological phenotype, clinical outcomes data onto single platform for multi-dimensional comparison and analysis
Used SAS Base, ARRAY, PROC/IMPORT, EXPORT, FORMAT, TRANSPOSE, string functions for calculating, formatting, transposing and normalizing data
Developed SAS Macros to dynamically import file, transform, merge and export data
Worked closely with team lead to design, test, validate and manage the data auto-curation system. PROFESSIONAL EXPERIENCE
Research Associate
Duke University Medical Center (Durham, NC) 2013– 2015 At Preston Robert Tisch Brain Tumor Center, the primary goal of my project was to combine insights from large scale genomic data analysis with clinical studies, with a hope of translating scientific findings into discovery of novel therapeutic target and development of personalized therapy for brain cancers Responsibilities
Served as a study lead to configure project goals and scopes based on evidence orientated approaches and evaluation of long term benefit and risk
Integrated scientific insights from principal investigators, physicians and biostatisticians
Designed and implemented analytic framework for data measurement, validation and statistical analysis
Performed data loading, extraction and transformation and investigated data related errors, outliers, and missing values
Preprocessed and normalized data with R packages before feeding into statistical analysis
Characterized data distribution and correlation by exploring and visualizing data with R package ggplot2
Performed statistical analysis T-Test, ANNOVA, Chi-squared test for hypothesis testing, decision making at critical steps
Participated and presented status updates and scientific findings in the regular team meetings
Ensured compliance to HIPPA, laboratory SOPs regulations and internal standards such as templates and documentation standards
Coached graduate students and technicians for the study design and technical issues Research Fellow
Memorial Sloan Kettering Cancer Center (New York City, NY) 2010- 2013 The Human Oncology and Pathogenesis Program HOPP at Memorial Sloan aims to advance scientific knowledge while bridging discoveries made in the laboratory with those made in the clinic. At HOPP, I was involved in projects that aim to explore and translate molecular and genetic insights into breast and kidney cancer therapeutic intervention.
Responsibilities
Participated in conceptualizing study proposal and analytic framework, and broke down project plan into stepwise actionable workflows
Performed data mining in a variety of medical databases, integrated empirical evidences from different resources and defined guidelines for data measurement and collection
Enforced data consistency and accuracy by standardizing the practice of data collection, transformation and management process
Conducted data aggregation, synthesis, explorative analysis to understand patterns and trends within data
Visualized data trending and pattern with histogram, bar chart, scatter plot and box plot etc.
Identified correlation between clinical, genetic and biological outcomes features
Standardized documentation of study protocols, data dictionary, status and scientific reports
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