RECENT WORK EXPERIENCE

Senior Data Scientist                                                                              Dec 2016 – Present

AT&T, Chief Data Office                                                                                                                                                                                          

Collaborated with senior business leaders and technical team to identify opportunities for retail optimization; proposed methods for retail evaluation and extraction of actionable insights to drive revenue growth

  • Designed pilot study for testing proposed solutions in retail locations

  • Created visualizations to communicate study performance metrics to senior business leaders and technical team

  • Performed data exploration and data cleaning to facilitate development of prediction models

  • Developed and validated classification models using machine learning algorithms    

Research Associate (Assistant Professor)                                            Aug 2011 - Present

The University of Chicago, Biostatistics Laboratory                        http://bit.ly/spw-uchicago

Consulted with over 110 biomedical research teams in The University of Chicago Medical Center, designing clinical research studies (sample size calculation and analysis plan development), analyzing study data, and summarizing results for the study team and greater scientific community.

  • Developed a survival probability prediction equation for patients on the national lung transplant waiting list given missing covariate data and a large number of highly correlated features. Compared to other published survival prediction models for this population, survival estimates obtained using the novel approach more closely resembled Kaplan-Meier estimates at 1, 2, and 5 years.

Relevant skills/tools: bootstrap, model validation, elastic net                                   http://bit.ly/spw-survival-prediction

  • Developed a missing data imputation algorithm for interval censored count covariate data used to examine the relationship between overall survival and rate of disease progression.

Relevant skills/tools: mixed effects model, joint longitudinal-survival model                                           http://bit.ly/spw-jointmodel

  • Investigated the changes in levels and trends of market share of popular attention-deficit hyperactivity disorder (ADHD) treatments after three FDA public health advisories using segmented time series regression models.

Relevant skills/tools: generalized least squares regression                                                          http://bit.ly/spw-adhd

  • Designed and implemented a simulation study of a mixed-effects location scale model [http://bit.ly/spw-mixregls]. Significantly reduced run time by simulating data in Python (within R) and parallelizing across blocks of simulated datasets using 16 processors and 70 GB RAM on a Linux-based cluster node.

Relevant skills/tools: Python, parallel computing                                                                     (manuscript in progress)

  • Served as Principal Biostatistician for a 5 year longitudinal biomarker study of wall shear stress as a candidate predictor for cephalic arch stenosis. Designed a customized REDCap database for mixed-mode patient study data and created customized dashboard reports.

Relevant skills/tools: survival analysis, data management                                                                      http://bit.ly/spw-hammes-cas

Graduate research assistant: Los Alamos National Laboratory                           May 2009 - Jul 2011

Division of Theoretical Biology and Biophysics                                        http://bit.ly/spw-hiv

 

Biostatistician for an international multi-disciplinary, multi-institutional team of HIV vaccine researchers testing theoretical design strategies in a remote animal research laboratory. Duties include analysis of immune response data, presentation of study findings to research team, and production of high-quality figures for team leader’s conference presentations and journal submissions.

  • Compared immune responses elicited from several candidate vaccine design strategies and select a subset of vaccines to be tested in the next iteration of vaccine trials.

  • Developed a Bayesian Poisson fixed- and mixed-effects regression models for interval censored HIV vaccine immune response counts (dissertation: http://bit.ly/2bfpJQk).

© 2016 by Sydeaka P. Watson