Data Scientist/Data Analyst

BRANDON O’GRADY

**************@*****.***

**** * **** ** • Houston, Tx • 806-***-**** • /n/brandonogrady

OBJECTIVE

Recent Biostatistics graduate eager to start my career where I can implement my strong research and analytical skills to build mathematical models and solutions.

EDUCATION

The University of Texas

Health Science Center

at Houston

Texas A&M University Masters of Science: Biostatistics

Minor: Epidemiology

Bachelors of Science: Allied Health December 2020

December 2017

WORK EXPERIENCE

UT M.D. Anderson Cancer Center– Graduate Research Assistant; Houston, TX December 2019-December 2020

• Extracted retrospective data related to demographics, cancer diagnosis, treatments received, dates of computed tomography scans, and patient survival and disease recurrence outcomes for 800 cancer patients

• Entered data into a REDCap database and provide periodic summary reports of the data in R-Studio

• Review CT scans for quality of the images, location, and size of tumors

UTHealth Auxiliary Enterprises - Recreation Center – Student Worker; Houston, TX August 2018-November 2019

• Enforced all departmental policies and procedures

• Processed membership transactions

• Help answer any questions or requests members have

Certificates

IBM Data Analyst Professional Certificate January 2021

IBM Data Science Professional Certificate February 2021

PROJECTS

Thesis – Survival Analysis of Colorectal Cancer Patients with Liver Metastasis; R-Studio Fall 2020

• Conducted a univariate analysis and K-sample comparison to investigate survival outcomes and liver recurrence

• Conducted a semi-parametric and a refined Cox model to detect prognostic factors for survival

• Conducted a competing risk regression to investigate liver recurrence

• R Packages used: survival, tidyverse, ggplot2, dplyr, and cmprsk

Course Project (Regression Techniques) – Predictors of ICU Length of Stay in Sarcoma Patients; SAS Spring 2019

• Accessed the four key assumptions for the linear regression model with the Shaprio-Wilk Test and visual plots

• Conducted a Box-Cox analysis for the best transformation of the outcome variable

• Employed an Akaike information criterion, Schwarz-Bayesian, and Mallow’s CP to determine a final model

• Validated each model by using the cross-validation method using a training set (70%) and testing set (30%)

LEADERSHIP EXPERIENCE AND ACTIVITIES

Biostatistics and Data Science Student Association – Former member January 2019-December 2020

• Help organize Biostatistics and Data Science seminars

• Support and help fellow biostatistics students

• Attend monthly meetings

SKILLS __

• Computer Skills: MS Office, Power BI, Python, R, REDCap, SAS, STATA, SQL, and Tableau

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