Shortly after I learned LaTeX I used it to write my resume (or CV if you will), freeing me from the headache of using Microsoft Word and the associated formatting troubles. Even that wasn’t enough though because different audiences needed different information and job listings. I could have stored all the information in the file and commented out bullet points I did not want to use, but that seemed sloppy. So instead I wrote an R package called resumer.

The trick is to store all of the data in a CSV, one row per bullet point.1

JobName Company Location Title Start End Bullet BulletName Type Description
Tech Startup Pied Piper New York, NY CTO 2013 Present Set up company’s computing platform 1 Job NA
Tech Startup Pied Piper New York, NY CTO 2013 Present Designed data strategy overseeing many datasources 2 Job NA
Tech Startup Pied Piper New York, NY CTO 2013 Present Constructed statistical models for predictive analytics of big data 3 Job NA
Large Bank Goliath National Bank New York, NY Quant 2011 2013 Built quantitative models for derivatives trades 1 Job NA
Large Bank Goliath National Bank New York, NY Quant 2011 2013 Wrote algorithms using the R statistical programming language 2 Job NA
Bank Intern Goliath National Bank New York, NY Intern 2010 NA Got coffee for senior staff 1 Job NA

Each row represents a detail about a job. So a job may take multiple rows.

The columns are:

  • JobName: Name identifying this job. This is identifying information used when selecting which jobs to display.
  • Company: Name of company.
  • Location: Physical location of job.
  • Title: Title held at job.
  • Start: Start date of job, usually represented by a year.
  • End: End date of job. This would ordinarily by a year, ‘Present’ or blank.
  • Bullet: The detail about the job.
  • BulletName: Identifier for this detail, used when selecting which details to display.
  • Type: Should be either Job or Research.
  • Description: Used for a quick blurb about research roles.

There are many parts to using this package which are all explained in the README and mostly reproduced here.

The yaml header holds your name, address, the location of the jobs CSV file, education information and any highlights. Remember, proper indenting is required for yaml.

The name and address fields are self explanatory. output takes the form of package::function which for this package is resumer::resumer.

The location of the jobs CSV is specified in the JobFile slot of the params entry. This should be the absolute path to the CSV.

These would look like this.

---
name: "Generic Name"
address: "New York"
output: resumer::resumer
params:
    JobFile: "examples/jobs.csv"
---

Supplying education information is done as a list in the education entry, with each school containing slots for school, dates and optionally notes. Each slot of the list is started with a -. The notes slot starts with a | and each line (except the last line) must end with two spaces.

For example:

---
education:
-   school: "Hudson University"
    dates: "2007--2009"
    notes: |
        GPA 3.955  
        Master of Arts in Statistics
-   school: "Smallville College"
    dates: "2000--2004"
    notes: |
        Cumulative GPA 3.838 Summa Cum Laude, Honors in Mathematics  
        Bachelor of Science in Mathematics, Journalism Minor  
        The Wayne Award for Excellence in Mathematics  
        Member of Pi Mu Epsilon, a national honorary mathematics society
---

To provide a highlights section set doHighlights: yes and create a highlights tag.

Each bullet in the highlights entry should be a list slot started by -. For example.

---
doHighlights: yes
highlights:
-   bullet: Author of \emph{Pulitzer Prize} winning article
-   bullet: Organizer of \textbf{Glasses and Cowl} Meetup
-   bullet: Analyzed global survey by the \textbf{Surveyors Inc}
-   bullet: Professor of Journalism at \textbf{Hudson University}
-   bullet: Thesis on \textbf{Facial Recognition Errors}
-   bullet: Served as reporter in \textbf{Vientiane, Laos}
---

Jobs and details are selected for display by building a list of lists named jobList. Each inner list represents a job and should have three unnamed elements: – CompanyNameJobName – Vector of BulletNames

An example is:

jobList <- list(
    list("Pied Piper", "Tech Startup", c(1, 3)),
    list("Goliath National Bank", "Large Bank", 1:2),
    list("Goliath National Bank", "Bank Intern", 1:3),
    list("Surveyors Inc", "Survery Stats", 1:2),
    list("Daily Planet", "Reporting", 2:4),
    list("Hudson University", "Professor", c(1, 3:4)),
    list("Hooli", "Coding Intern", c(1:3))
)

Research is specified similarly in researchList.

# generate a list of lists of research that list the company name, job name and bullet
researchList <- list(
    list("Hudson University", "Oddie Research", 4:5),
    list("Daily Planet", "Winning Article", 2)
)

The job file is read into the jobs variable using read.csv2.

library(resumer)
jobs <- read.csv2(params$JobFile, header=TRUE, sep=',', stringsAsFactors=FALSE)

The jobs and details are written to LaTeX using a code chunk with results='asis'.

Same with research details.

Regular LaTeX code can be used, such as in specifying an athletics section. Note that this uses a special rSection environment.

\begin{rSection}{Athletics}
\textbf{Ice Hockey} \emph{Goaltender} | \textbf{Hudson University} | 2000--2004 \\
\textbf{Curling} \emph{Vice Skip} | \textbf{Hudson University} | 2000--2004
\end{rSection}

A complete template is available when creating a new file in RStudio.

Any suggestions or, even better, pull requests are welcome at the GitHub page.


  1. A helper function, createJobFile, creates a CSV with the correct headers.

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Jared Lander is the Chief Data Scientist of Lander Analytics a New York data science firm, Adjunct Professor at Columbia University, Organizer of the New York Open Statistical Programming meetup and the New York R Conference and author of R for Everyone.

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