CV
Education
- B.S. in Mathematics, University of Miami, 2014-2018
- Ph.D in Data Science, New York University, 2021-2026 (expected)
Work experience
Research Analyst in the Center for Computational Biology : Simons Foundation Flatiron Institute (2018-2021) - Designed algorithms to predict gene regulatory network interactions from genome-wide data
- Developed, optimized, and maintained software pertaining to the network inference method the Inferelator
- Adapted the Inferelator software to newly developed single-cell sequencing technologies
- Explored and implemented mathematical models for exploratory analysis of biological data and estimation of latent biophysical parameters unable to be quantified using current sequencing technologies.
- Developed Python software for implementing computing techniques such as multiprocessing and Dask analytic engine, which parallelizes computational cores on high-performance clusters at the Simons Foundation
- Identified appropriate experimental designs for inferring gene regulatory networks to answer biological questions at hand within the following organisms: B. subtilis, S. cerevisiae, M. musculus, and D. melanogaster
- Collaborated with wet-lab scientists in the Desplan Lab to infer single-cell gene regulatory networks within several time points and cell types of the developing Drosophila Optic lobe
- Designed algorithms to predict gene regulatory network interactions from genome-wide data
Research Intern in the Center for Computational Biology : Simons Foundation Flatiron Institute (Summer 2017) - Data cleaning: used Python and R to convert raw unstructured data into organized data-frames for analysis
- Manipulated large Twitter datasets of over 250GB through parallel processing
- Quantitative text analysis: performed sentiment analysis using dictionary-based methods
- Inferential statistics: modeled trends in sentiment following key political events (e.g., the 2016 U.S. presidential election) through non-parametric enrichment analyses
- Data visualization:
- Plotted non-parametric enrichment results to display trends in sentiment in reaction to key political events
- Designed multidimensional heat maps to compare the strength of ideological and event related influences on the content of a speaker’s language over time
- Data cleaning: used Python and R to convert raw unstructured data into organized data-frames for analysis
- Investment Banking Summer Analyst : Atlas Advisors (Summer 2016)
- Performed holistic analysis of a U.S. accessible luxury company to determine the optimal strategy for operating the company
- Constructed a three-statement DCF projection model
- Estimated company’s weighted average cost of capital and valued cash flows by DCF
- Conducted trading multiples valuation of target
- Analyzed historical and projected sources and uses of cash to determine the optimal use of surplus cash
- Analyzed EVA to determine target’s value creation for shareholders
- Assisted in the creation of strategic alternatives presentation for a separate U.S. accessible luxury company
- Analyzed U.K. bid premiums in public transactions over $100MM since 2013
- Performed holistic analysis of a U.S. accessible luxury company to determine the optimal strategy for operating the company
- Investment Banking Summer Analyst : Atlas Advisors (Summer 2015)
- Researched and profiled personal care multilevel marketing companies in emerging markets
- Analyzed and developed financial projections to value a Peruvian department store company using discounted cash flows and comparable company trading multiples
- Analyzed the industry trends and financial performance of luxury merchandise companies and prepared presentation to client for a potential merger
Languages
- Programming Languages:
- Python
- R
- Java
- Unix
- HTML
- SQL
- PyTorch/Pyro
- Spoken Languages
- English (native speaker)
- French (advanced)
Teaching
- Teaching Assistant
- NYU CDS US-DA 206 (Summer 2022 & Summer 2023)