Statistician Resume

SUMMARY:

5+ Years with Python and R
Data mining, Web scraping, Regular expression
Statistic models: A/B testing, Linear/Logistic Regression, ANOVA, Nonparametric, Time Series, Bayesian Inference and more
Machine learning models: Random Forest, Boosting, SVM, K - means and Hierarchical Clustering, Topic Modeling (NMF, PCA), NLP.
Proficient with SQL, SPSS, MongoDB
Familiar with AWS, MapReduce, Spark

PROFESSIONAL EXPERIENCE:

Statistician

Confidential

Responsibilities:

Publication company of standardized assessment materials.
Built highly reliable (Cronbach’s alpha > 0.9) assessment test model for large-scale, country-wide validation through applying item response, structural equation and factor analysis models in R.
Automated cleaning, validation and analytic processes of psychometric data by developing functions in R using regular expression, sped up data cleaning procedure from 10+ hours to seconds and reduced data cleaning error rate from 10% to less than 1%.

Data Analyst, Quality Assurance

Confidential

Responsibilities:

Geographic Information System service provider.
Compiled and delivered business intelligence data to project managers through mining and scraping data from various web pages and API using Python.
Brought clarity of project progress to project managers by providing detailed monthly query, report, and analysis of KPI metrics using SQL.