resume.Rmd

---
name: Nathaniel Price, Ph.D.
address: Washington, D.C.
phone: +1 904 315 2486
email: natbprice@gmail.com
website: natbprice.github.io
geometry: left=1in,right=1in,top=1in,bottom=1in
bibliography: publications.bib
nocite: |
  @price_open-sourced_2020, @balesdent_advanced_2016, @chaudhuri_nasa_2015
knit: (function(input, ...) {
    c(rmarkdown::render(
      input,
      output_format = "github_document",
      output_file = "README",
      envir = globalenv()
    ),
    rmarkdown::render(
      input,
      output_format = "pdf_document",
      output_file = "nprice_resume",
      envir = globalenv()
    ))
  })
output:
  pdf_document:
    extra_dependencies:
      fontawesome: null
      carlito: sfdefault
      fancyhdr: null
  github_document: default
---

```{r setup, include=FALSE}
knitr::opts_chunk$set(echo = FALSE)
library(fontawesome)
library(rmarkdown)
```

\vspace*{-0.75in}
\thispagestyle{empty}
\centerline{\huge \bf `r metadata$name`}
\vspace{5pt}
\centerline{
\faicon{map-marker} `r metadata$address` \hspace{2 pt}
\faicon{phone} \href{tel:`r gsub("[[:space:]]", "", metadata$phone)`}{`r metadata$phone`} \hspace{2 pt}
\faicon{envelope} \href{mailto:`r metadata$email`}{`r metadata$email`} \hspace{2 pt}
\faicon{home} \href{https://`r metadata$website`}{`r metadata$website`}
}
\vspace{5pt}
\hrule

\pagestyle{fancy}
\fancyhead[L]{\textcolor[gray]{0.4}{Resume: `r metadata$name`}}
\fancyfoot[L]{\textcolor[gray]{0.4}{Document compiled on `r Sys.Date()` (\href{https://www.github.com/natbprice/resume}{github.com/natbprice/resume})}}
\pagenumbering{gobble}

```{r, results='asis', eval = knitr::is_html_output()}
cat("# ", metadata$name, "\n")
fa("map-marker")
cat("   ", metadata$address, "   ")
fa("phone")
cat("   ", metadata$phone, "   ")
fa("envelope")
cat("   ", metadata$email, "   ")
fa("home")
cat('&nbsp;&nbsp;&nbsp;<a href="https://',
  metadata$website,
  '">',
  metadata$website,
  "</a>",
  "&nbsp;&nbsp;&nbsp;",
  sep = ""
)
cat("<hr/>")
```


## Experience

**ICF**, Reston, Virginia, US (Remote) \
*Lead Data Scientist* | March 2022 - Present \
*Senior Data Scientist* | May 2020 - March 2022 \
*Data Scientist* | October 2019 - May 2020

- Built Azure cloud computing/machine learning infrastructure from the ground up for low-cost, scalable analysis of billions of records of utility smart meter data
- Researched, prototyped, and deployed machine learning models related to utility analytics (e.g., energy disaggregation, energy savings, EV detection)
- Established cross-team Data Science Knowledge Share meetings to promote collaboration and information sharing
- Assisted other teams in scaling data science processes by advising on best practices and providing technical assistance

**University of Nebraska-Lincoln**, Lincoln, Nebraska, US \
*Data Scientist* | September 2016 - October 2019

- Designed, developed, and deployed open-source, web-based, data analysis application (SQL, R, Shiny) for analyzing repeat-purchase behavior (recruitment, retention, churn, reactivation) of Nebraska sportspersons
- Mentored graduate students and facilitated data science research resulting in multiple journal publications, international conference presentations, and a book chapter

**University of Florida**, Gainesville, Florida, US \
*Graduate Research Assistant* | August 2012 - July 2016

- Integrated machine learning (e.g., Gaussian process) and optimization to design engineering systems considering uncertainty in future decision making process
- Collaboratively developed optimization-based solution to The NASA Langley Multidisciplinary Uncertainty Quantification Challenge (2014)

**ONERA - The French Aerospace Lab**, Palaiseau, Île-de-France, France \
*Ph.D. Student Researcher* | October 2014 - March 2016

- As part of international joint-PhD collaboration between 2 universities (UF, EMSE) and ONERA aerospace lab, developed a novel method for optimal design under uncertainty that incorporated risk of future redesign into design optimization
- Co-authored book chapter on advanced space vehicle design under uncertainty

**University of Florida**, Gainesville, Florida, US \
*Undergraduate Research Assistant* | September 2011 - August 2012 

- Created parameterized biomechanical model in Python to understand interactions of patient variability and design changes on safety of Biomet rigid sternal fixation device
- Awarded Biomedical Engineering Society (BMES) Design and Research Award and Knox T. Millsaps Outstanding Undergraduate Paper Award

**SpaceX**, Cape Canaveral, Florida, US \
*Launch Engineer Intern* | August 2010 - January 2011

- Performed maintenance of launch vehicle ground systems
- Ground crew team member during launch of SpaceX COTS Demo Flight 1

## Education

**Doctorate | Mechanical Engineering** \
*University of Florida*, Gainesville, Florida, US | 2016 \
*École des Mines de Saint-Étienne*, Saint-Étienne, Rhône-Alps, France | 2016

**Graduate Certificate | Scientific Computing** \
*University of Florida*, Gainesville, Florida, US  | 2014

**Master of Science | Mechanical Engineering** \
*University of Florida*, Gainesville, Florida, US | 2014

**Bachelor of Science | Mechanical Engineering** \
*University of Florida*, Gainesville, Florida, US  | 2012

## Professional Development

- DeepLearning.AI TensorFlow Developer Professional Certificate (80 hours), Coursera, Credential ID [VDW7KD9SA2TM](https://coursera.org/verify/professional-cert/VDW7KD9SA2TM) (2023)
  
## Publications

```{r, results = "asis"}
fa('book')
cat("&nbsp;&nbsp;&nbsp;2 book chapters&nbsp;&nbsp;&nbsp;")
fa('scroll')
cat("&nbsp;&nbsp;&nbsp;5 peer-reviewed journal publications&nbsp;&nbsp;&nbsp;")
fa('file-alt')
cat("&nbsp;&nbsp;&nbsp;5 conference papers&nbsp;&nbsp;&nbsp;")
```


Full List Available On Google Scholar: https://scholar.google.com/citations?user=rXaKU0EAAAAJ&hl=en

**Select Publications:**

<div id="refs"></div>

## Data Science Skills
**Cloud Computing:** Azure • AWS • high-performance computing (Azure Batch) • NoSQL (Azure Table/Blob, AWS S3) •
containers (Docker, Azure ACI, Azure ACR) \
**Communication:** presentations • dashboard design (Shiny) • data analysis reports (Rmarkdown, Jupyter) • data visualization (plotly, ggplot2, leaflet) • peer-reviewed publications (journal, book chapter, conference) \
**Numerical Methods:** optimization (stochastic, genetic, multi-start) • differential equations \
**Programming Languages:** R • Python • SQL • Matlab • C++ \
**Software Development:** source control (Git, SVN) • agile development (Jira) • CI/CD (Azure DevOps) \
**Statistics & Machine Learning:** deep learning (Tensorflow) • NLP • surrogate models • uncertainty quantification • Monte Carlo simulation • experimental design • survey methodology \