Statistical Analyst Resume Example
- Hard-working Statistician, with strong knowledge in statistical theories and formulations, and proficiency in statistical modeling process
- Two years experience in developing analytical research studies and business projects for data insights and decision making
- Proficient in data preparation, including compiling, sampling, cleaning, transformation, etc.
- Proficient in statistical programming with R, SAS and matlab, with advanced SAS programmer for SAS 9 certification
- Strong passion and commitment in risk management and financial industry
Conducted quantitative analytics and modeling projects based on the business challenges that the clients proposed, who are generally local non-profit organizations, investigating the operational influence and understanding the near-term market trends
- Tracked, collected, analyzed and interpreted trends/ fluctuation in data from legal business, education, public service, etc.
- Provided professional writing and interpretative reports at each step, starting with proposals, then protocols, conclusive thesis, presentations and other documents as required for internal documentation and external clients' collaboration
- Worked directly with HOMELine, a non-profit organization who provides legal service, to develop a strategy that provides their tenants with maximum benefits
Assisted with the undergraduate levels Statistics courses to 100-120 students. Held office hours; lectured lab sections; graded for homework/exams and provided insightful feedbacks
- Developed and implemented interesting and interactive presentations to increase student understanding of course materials
- Managed to provide high-quality lectures while keeping my own academic record, successfully participating in research studies and actively involved in volunteer work
Provided statistical expertise to help clients with the root cause and insights on their specialized fields. Performed advanced statistical techniques as the guidance to their decision making.
- Designed the split-plot experiment and performed the planting under different natural conditions and enemy types. Inspected the various plants' growth rates and volumes. Conducted ANOVA modeling, testing and variance analysis to explore the insights
- Developed the model and searched for the appropriate approach individually with minimum assistance from the supervisor, while constantly checking in with the clients and asking for feedback and suggestions
Coordinated within business department, joining the risk management team to perform investment portfolio analysis and evaluation.
- [Database warehouse] Monitored and analyzed KPI and financial ratios
- Delivered informational businesses and products presentations to potential investors to build symbiotic client relationships
- Created monthly PowerPoint presentations illustrating business performance and objectives of the next stage
- 4.0 out of 4.0 GPA
- Outstanding student award: 2014 and 2015
- Minor in International Trading
- 3.6 out of 4.0 GPA
Statistical techniques-
- Data management: querying, filtering, extraction, visualization, managing unstructured dataset and dataset with missing values
- Regression and classification: linear/non-linear regression, logistic regression, mixed-effect models, robust analysis
- Multivariate analysis: PCA/LDA, model selection with regularization
- Data mining and Machine learning algorithms for 'Big data': cluster, decision tree, artificial neural with multilayer perceptrons, kernel machine, hidden Markov model
- Time series analysis: SARIMA/ARIMA, VAR, GARCH and other state-space models, spectral and frequency analysis
Programming-
- Statistical programming: SAS, R, S-plus, Matlab, Python
- Database management system: Oracle SQL
Language-
- Bilingual: read, write and speak with both English and Mandarin Chinese
Dissertation: "Robust estimation of parameters for standardizing neuropsychological tests with applications to data from the SMART study"
continued Professor Birgit Grund's SMART study on neurocognitive performance of HIV-positive patients and tried to find out the best approach to standardize the data. Robust analysis was performed and the difference of OLS, M-estimator, S-estimator and MM-estimator were compared and studied. Statistical significance and effect size were combined to find the best model. High-leverage points were investigated using simulation study
Dissertation: "An exploratory study on potential risk factors of heart disease"
developed logistic regression and statistical techniques in model selection such as cross validation regularizations to study the risk factors of heart disease. In addition, the paper proposed several insightful suggestions based on the analysis.
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Resume Overview
School Attended
- University of Minnesota, Twin Cities
- Beijing Normal University
Job Titles Held:
- Statistical Analyst
- Teaching Assistant
- Statistical Consultant
- Junior Associate - [Risk Management]
Degrees
- Master of Science : Statistics
Bachelor of Science : Mathematics and Statistics
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