Experience

Flatiron Health - Research Sceintist, Statistical Programmer

Oct 2025–Present

Built and maintained reproducible pipelines to analyze real-world oncology data, enabling predictive modeling of treatment patterns and outcomes.
Applied statistical and machine learning methods to high-dimensional clinical datasets to generate actionable insights for research and decision-making.

RTI International — Bioinformatics Data Scientist

Oct 2022–Oct 2025

Applied supervised classification models across harmonized variant datasets (gnomAD, dbSNP, TOPMed, GenomeAsia) to predict pathogenicity of VUS and model population-level disease risk.
Engineered scalable pipelines for eQTL and biomarker discovery integrating genetic and transcriptomic data to identify signatures relevant to substance use disorder.
Designed and deployed RAG + semantic clustering frameworks to accelerate knowledge extraction from literature for gene–phenotype interpretation.
Partnered with clinicians and biologists to ingest, harmonize, and visualize metagenomic, metabolomic, and clinical assay datasets; delivered QA dashboards for stakeholders.

Duke University — PhD Researcher

Dec 2018–Oct 2022

Built reproducible pipelines for RNA-seq, ChIP-seq, and DNase enabling ML/statistical modeling.
Revealed regulatory mechanisms of neuronal plasticity in development and addiction through integrative transcriptomic + epigenomic modeling.
Applied conditional Gaussian Bayesian networks to identify coordinated epigenetic regulation across loci.

ScitoVation — Computational Toxicology Intern

Jan 2017–Jan 2018

Centralized and harmonized 45K+ chemical assay datasets, applying ML/statistical clustering methods in Python/R to model compound bioactivity and prioritize chemical risks, supporting predictive toxicology workflows.
Automated literature review and data curation tasks using Python and the PubMed API, streamlining the process of gathering and analyzing public datasets on chemical bioactivity for risk assessment.

NC Museum of Natural Sciences — Invertebrate Research Intern

Jun 2016–May 2017

Collected, digitized, and harmonized morphometric data across multiple museum collection units, standardizing measurements from hundreds of invertebrate specimens to enable comparative analysis.
Developed regression based framework to integrate morphometric and genotype data for species delimitation, providing critical insights into crayfish species identification and preservation strategies.

NC Central University — Research Technician

Jun 2015–Dec 2016

Developed the MonoInc R package for monotonic imputation (regression-based and nearest‑neighbor methods).
Conducted genetic & epigenetic association analyses for asthma, including QC, normalization, and covariate modeling.

NC State University — Undergraduate Researcher

Jun 2016-Aug 2016

Evaluated differential gene expression in Arabidopsis thaliana to study lignin biosynthesis, using R for data analysis to identify key genes and pathways regulated in this process.
Integrated transcriptomic data into differential equations models to simulate molecular expression, contributing to the development of synthetic systems for lignin production, a key component in biofuel development.

Education

Duke University — PhD, Computational Biology & Bioinformatics

2022

Research focused on multi‑omic integration and probabilistic modeling; built scalable HPC pipelines for sequencing data.
BioCoRE IMSD Scholar
First Black woman awarded PhD in Comp Bio & Bioinformatics at Duke University

Meredith College — BS Mathematics & BS Biology, Magna Cum Laude

2017