Data Scientist Resume

WORK EXPERIENCE:

Data Scientist

Confidential

Responsibilities:

Provide insights to customers of Confidential re: shipment details, customs clearance, and percentage of clearance.
Develop KPIs/SQIs for process improvement for overall entry level Confidential employees using mathematically techniques such as Mahalanobis distance.
Create predictive models that provide insights on shipment/pieces that reach pre - clearance based on origin, destination, and seasonal effects.
Provide dashboards and data visualization using SAS Visual Analytics and graphics vis R Shiny/ggplot2.
Languages and tools: R, SAS, SAS VA, machine learning, decision trees, cluster analysis, predictive analytics

Data Science Consultant

Confidential

Responsibilities:

Lead initiative on project and project life cycle to analyze 100 GB of proprietary data from Fortune 100 Company.
Purpose was to identify significant features associated with maximization of revenue.
Utilized machine learning techniques such as cross validation, Lasso regression, and linear regression.
Created a GUI for easy feature selection that utilizes machine learning model above.
Deliverables are expected to be completed by end of the year.
Provide updates, reports, and dashboards for company.
Languages and tools: R, statistical programming, Lasso regression, bootstrap, cross validation

Research Data Specialist

Confidential

Responsibilities:

Created database that stores data from cancer treatment protocols using customized VBA.
Primary database administrator using SQL statements to extract data prior to analysis in SAS and R.
Provide reports and dashboards for protocol updates and Confidential t progress through interventions.
Implemented imputation methods along with non-parametric techniques for protocol objectives.
Analyzed Confidential t text responses using Multidimensional Scaling.

Data Scientist Consultant

Confidential

Responsibilities:

Analyzed large volumes of genomic data to locate associations with diseases.
850,000 DNA sites sequenced from 2000 persons with 326 variables collected per person.
Utilized R to iteratively use logistic regression to find significant associations between 548 different CPG sites and associations with asthma and covariates.
Used Lasso regression for significant variable selection out of 326 variables.
28 out of 548 CPG sites were shown to be significantly associated with asthma outcome.
Prepared a comprehensive statistical report which included R generated figures.
Languages and tools: R, Glmnet, Lasso regression, logistic regression, SAS, Python, statistical programming

Research Statistical Consultant

Confidential

Responsibilities:

Analyzed 14 GB of electrophysiological brain data via MATLAB and Neuroscan Curry.
Created customized MATLAB scripts for matrix manipulation of 21 x 68 x 1,000,000 data.
Utilized PCA dimensionality reduction prior to data analysis.
Analyzed data using SAS mixed modeling with Tukey post-hoc test adjusting for multiple comparisons.
Prepared comprehensive statistical report for supervisor which included R figures and plots.
Language and tools: MATLAB, R, SAS, PCA, mixed modeling, glm, Neuroscan Curry, statistical programming

Data Scientist Consultant

Confidential

Responsibilities:

Provided statistical support for experimental designs such as nested RBD.
Analyzed significant features associated with performance outcomes using GBC.
Analyzed changes in proportions of reported outcomes using Cochran-Armitage Trend Test.