Candidate Information Title On-Site Data Analyst Target Location US-NJ-Jersey City Email Available with paid plan	20,000+ Fresh Resumes Monthly     View Phone Numbers     Receive Resume E-mail Alerts     Post Jobs Free     Link your Free Jobs Page     ... and much more Register on Jobvertise Free
Search 2 million Resumes Keywords: City or Zip:	Related Resumes

EducationNew York University - M.S. in Biostatistics Sep Street Address  - May 2024Shenzhen University - B.S. in Statistics Sep 2018 - Jun 2022 SkillsProgramming: SAS (SQL, Macro, Stat, Graph, ODS), R (Shiny), Python, SQL, MATLAB, C++ Data Tools: STATA, Tableau, MySQL, MS SQL Server, AWS RDS, Power BI, SPSS, Microsoft office Certifications: SAS Base + Advanced Programming, Biomedical Research  Basic/Refresher  CITI Program Professional ExperienceNYU School of Global Public Health New York, US (On-site) Teaching Assistant Mar 2024 - Apr 2024 Facilitated weekly SAS programming labs and provided one-on-one tutoring for 30+ graduate students, focusing on data manipulation, statistical analysis, and graphical representation pertinent to clinical research. Conducted the transformation of raw data into actionable insights for student projects in SAS using MERGE, SORT, and DO LOOP in DATA steps and PROC SQL, FORMAT, SUMMARY, FREQ, etc. NYU School of Global Public Health + NYU Langone Health New York, US (On-site) Biostatistical Student Consultant Jan 2023 - Apr 2023 Assisted with principal investigators to developed statistical analysis plans to assess the prognostic value of Acute Myeloid Leukemia (AML) patients before and after allo-HSCT; documented proceedings and actions from collaborative meetings. Created SAS programs to develop analysis-ready data sets from raw .csv data by performing import, set, and sort steps and performed various merging process within data step and PROC SQL step for 500+ AML patient records. Conducted AML patient survival analysis, employing the Kaplan-Meier methods using PROC LIFETEST and the Cox proportional hazard model using PROC PHREG to examine time-to-event data (e.g. death or relapse). Applied PROC LOGISTIC, PROC TTEST, and PROC ANOVA for association estimation between the event and potential factors; Generated figures such as box plot, forest plot, and scatter plot using PROC SGRENDER, PROC TEMPLATE and PROC SGPLOT. W-STANDARD USA California, US (Hybrid)Data Intern Dec 2022 - Apr 2023 Assisted with lead data analyst to conduct data visualization and utilize regression models and cluster analysis to segment dealer performance and identify key factors impacting sales by integrating R packages (dplyr, caret, ggplot2), increasing targeted sales by 15% by pinpointing underperforming regions and suggesting tailored marketing efforts. Worked closely with marketing and BI team to developed 3 Tableau dynamic dashboards for market analysis, product performance, and dealer/distributor evaluation, providing actionable business insights and quantify ROI. Logged daily activities, analyses, and findings into Jira by creating detailed tickets for each tasksuch as data checks, analysis reports, and dashboard updates, ensuring transparency and maintaining continuity in ongoing projects. Lalamove Shenzhen, CHN (On-site)Data Analyst Intern Dec 2021 - Aug 2022 Assisted with data scientist to utilize R packages (tidytext, topicmodels, dplyr) to preprocess customer complaints data(tokenization, stop word removal), performed LDA topic modeling wand sentiment analysis, and provided actionable insights leading to a 10% reduction in goods damage complaints. Collaborated with BI team to designed 3 Tableau dashboards featuring dynamic filters and interactive visualization for freight orders to showcase local government, ensuring compliance and safety that adhere to local policy, and subsequently supporting the acquisition of the local operation permits. Project ExperienceBiostatistics Masters Thesis: Machine Learning for Children Sleep States Classification Using Accelerometer Data Established a ML workflow using R for non-invasive pediatric sleep analysis using data from Child Mind Institute by integrating feature engineering and tree-based classification algorithms (Random Forest, LightGBM, XGBoosting); created interactive visualization with R shiny for data exploratory analysis and result presenting. Synthesized detailed research findings into a comprehensive report and delivered a persuasive oral presentation to a cross-disciplinary audience of investigators and graduate peers. Clinical SAS Statistical Programming Boot Camp Attended interactive learning sessions guided by industry professor, gaining insights into drug development process, CDISC standards, and data management principles in clinical trials. Led a capstone project on a phase II double-blind trial for ovarian cancer patients, creating and validating SDTM datasets for a mock regulatory submission, culminating in a well-received presentation of findings to industry experts. Yingyu (Jessica) Peng 201-805-0933 EMAIL AVAILABLE Linkedin Github