OVERVIEW

A data scientist with 8 years of experience applying machine learning algorithms and classical statistical modeling to derive insights from complex, high-dimensional data to optimize business strategies.

I excel at communicating complex machine learning and statistical modeling concepts and analysis results when collaborating with domain experts and business leaders.

KEY HIGHLIGHTS

Publications

Warren WC, … DeVogelaere E, … Eichler EE. Sequence diversity analyses of an improved rhesus macaque genome enhance its biomedical utility. Science. 2020

EDUCATION AND LICENSURE

University of California, Santa Cruz, Santa Cruz, CA                                       December 2019

Masters of Science in Bioinformatics

University of Arizona, Tucson, AZ                                                              December 2015
Bachelors of Science in Biological Systems Engineering, Spanish Minor

BPELSG Engineer in Training (EIT), Certificate No. EIT 157860, April 2016

SELECTED HONORS & AWARDS

PROFESSIONAL EXPERIENCE

Meta Platforms, Product Data Scientist, Austin, TX           11/21-present

• Create and manage targets for Revenue Operations teams' goals, proactively notify the teams of potential target misses, and perform exploratory data analysis to identify opportunities so we can still meet the targets
• Identified why extended credit customers pay late and proposed opportunities to improve payment behavior, resulting in a $200MM increase in free cash flow using linear regression, multiple seasonality decomposition, Theta and Prophet forecasting, and hypothesis tests with FDR correction
• Lead a 0-to-1 initiative to measure incremental progress towards preventing financial non-compliance by estimating the probability of black swan events, the cost of worst-case scenarios, and the value of proactive preparation
• Design an A/B test to evaluate the hypothesis that higher risk increases revenue while meeting the company's risk threshold, and minimizes detectable differences between test and control groups
• Building a data-driven culture with the Sales Intelligence product team. Developing a metric and goal-setting framework that reliably measures the team's value and informs their strategy

Takeda Pharmaceuticals, Cell Therapies Data Scientist, Cambridge, MA               02/20-10/21

• Originated novel applications for machine learning algorithms and models (XGBoost, Louvain clustering) in Python to identify predictors of key performance metrics
• Employed hypothesis testing (ANOVA, goodness-of-fit) and dimensionality reduction (PCA, UMAP, PHATE) to identify underperforming manufacturing runs and abnormalities
• Communicated the significance of complex analytical results to research scientists and business leaders to inform project strategies

Takeda Pharmaceuticals, Cell Therapies Informatics Intern, Cambridge, MA               06/19-09/19

• Collaborated with interdisciplinary teams to identify custom in silico models and facilitate data-driven decisions
• Trained classifier models (logistic regression, random forest) on in vitro, preclinical, and product characterization data to identify effective drug therapies

Cognizant Technology Solutions, Project Manager, South San Francisco, CA                                 02/17 - 08/18

• Awarded “Best Customer-Facing App” in Amgen-Cognizant Hackathon for a mobile app that visualizes capacity and spending by facility, group, and cost center
• Developed an Oracle database structure (SQL/Spark) for a laboratory mobile app
• Led team for a full 6-month development cycle; coordinated with managers and end-users

Cognizant Technology Solutions, Business Analyst, Thousand Oaks, CA            01/16-02/17

• Led and managed 20 short- and long-term projects between technical developers and end-users

• Developed and maintained data visualization and statistical analysis applications (Python and XML) for drug target assay analysis

• Co-authored white paper on foremost business strategies for pre-clinical data integrity [URL]

ACADEMIC RESEARCH

Algorithm Development for Time-Series Analysis, UC Santa Cruz             09/18 – 12/19

• Improved model accuracy by 20% to identify novel upstream Open Reading Frames (uORFs) in 5’ Untranslated Regions (UTRs)  [URL]
• Designed a Hidden Markov Model to determine the confidence of each base call in MinION raw current data [URL]

Computer Vision with Microscope Images, UC Santa Cruz            04/19 –06/19

• Classified microscope images with 60% precision and 40% accuracy to show the impact of protein levels on the survival of patients with cancer (human accuracy is 70%)
• Implemented transfer learning using VGG16 to featurize microscope images of proteins in cells, reducing computational costs by 98.2%
• Trained a deep feedforward neural network (modified ResNet-50) on microscope images

Primate Genome Annotation, UC Santa Cruz            01/19 –04/19

Warren WC, … DeVogelaere E, … Eichler EE. Sequence diversity analyses of an improved rhesus macaque genome enhance its biomedical utility. Science. 2020

• Analyzed RNA-seq datasets using computational/statistical regression techniques in Python to annotate and identify new genes in the latest human genome assembly data
• Applied multi-breakpoint and A* graph search for sequence duplications and rearrangements.

COMMUNITY OUTREACH