kennedy-jack.Rmd

---
name: Dr. Jack
surname: Kennedy
date: "`r format(Sys.time(), '%B, %Y')`"
www: jcken95.github.io
github: jcken95
linkedin: jcken95
email: jckennedy18@gmail.com
position: statistician | data scientist | educator | all-round-nerd
headcolor: 0086b3 #414141
docname: curriculum vitae
output: vitae::awesomecv
header-includes:
  - \hypersetup{colorlinks = true, linkcolor = awesome, urlcolor = awesome}
---

```{r setup, include=FALSE}
knitr::opts_chunk$set(echo = FALSE, warning = FALSE, message = FALSE)
library(vitae)
source("R/helpers.R")
```

# Professional Summary

I am a PhD educated statistician and data scientist with experience in data science consultancy and training.


I enjoy finding data-driven solutions to challenging problems whilst maintaining and improving best practices.

# Experience

```{r experience}
ukhsa_experience <- c(
  "Develop and maintain reproducible analytical pipelines and data-driven products",
  "Construct forecasts and nowcasts for epidemiological surveillance",
  "Promoting a culture of writing clean, maintainable code and modelling pipelines"
)

jr_experience <- c(
  "Provide statistical consulting services to a broad range of clients",
  "Software development: contribute to production-ready R packages",
  "Teach statistical and programming concepts in R with best practices front and centre to academia, industry and government",
  "Outreach: organise the `North East Data Scientists' meetup and contribute to \\href{https://www.jumpingrivers.com/authors/jack-kennedy/}{company blog}" # nolint: line length linter.
)

intern_experience <- c(
  "Collaborated with NU Solve, Jumping Rivers and the Food and Agricultural Organisation (UN)",
  "Developed a model-based clustering approach to diagnose the sustainability of fish populations across the world",
  "Developed a bespoke R package to provide FAO with the tools to take the developed methods forward",
  "Provided a rapid scoping project for a large automotive manufacturer"
)

gta_experience <- c(
  "Providing one-to-one support via the university Maths-Aid service to students; queries ranging from `How to calculate a percentage?' to `Which test is most appropriate for my data?' and `How to solve this differential equation?'", # nolint: line length linter
  "Provided maternity cover for senior tutor: triaging and delegating Maths-Aid appointments",
  "Delivered lectures to undergraduate students on statistical topics",
  "Marked coursework in a timely manner"
)

work_experience <- tibble::tribble(
  ~job, ~start, ~end, ~employer, ~details,
  "Senior Data Scientist", "Feb 2024", "Today", "UKHSA", ukhsa_experience,
  "Data Scientist", "Jan 2023", "Jan 2024", "Jumping Rivers", jr_experience,
  "Data Scientist (intern)", "Jan 2022", "May 2022", "NU Solve", intern_experience,
  "Graduate Teaching Assistant", "Oct 2018", " Dec 2022", "Newcastle University", gta_experience
)
work_experience %>%
  detailed_entries(
    what = job,
    when = glue::glue("{start} - {end}"),
    with = employer,
    why = details,
    .protect = FALSE
  )
```

# Education

```{r education}
phd_notes <- c(
  "\\href{https://theses.ncl.ac.uk/jspui/handle/10443/6060}{Thesis}: Uncertainty Quantification for Stochastic Simulators with Application to Offshore Wind Farms", # nolint: line length linter.
  "Applied and developed Gaussian process based techniques to improve the efficiency of stochastic simulation experiments",
  "Research themes: Bayesian methods; Decision Analysis; Bayesian Optimisation; Emulation; Gaussian Processes",
  "\\href{https://academic.oup.com/jrsssc/article/72/3/608/7082690}{Published} in a leading Statistics journal"
)

undergrad_notes <- c(
  "Thesis: Multivariate Statistics \\& Machine Learning: An Application to Product Costing in Nissan",
  "Provided Nissan's finance team with a statistical and ML toolbox to help them understand their data; regression for fast product costing; dimension reduction and clustering for outlier detection", # nolint: line length linter.
  "Studied a range of mathematical and statistical topics: regression \\& statistical modelling; Markov models; time series; queuing theory; extreme value theory; flexible regression; multivariate methods" # nolint: line length linter.
)

edu <- tibble::tribble(
  ~degree, ~start, ~end, ~institution, ~details,
  "PhD Statistics", "2018", "2023", "Newcastle University", phd_notes,
  "MMathStat (First class)", "2012", "2018", "Newcastle University", undergrad_notes,
)
edu %>%
  detailed_entries(
    what = degree,
    when = glue::glue("{start} - {end}"),
    with = institution,
    why = details,
    .protect = FALSE
  )
```

# Technical & Professional Skills

```{r skills}
r_notes <- c(
  "Developed production-ready R packages as part of a team",
  "Proficient with base R and {tidyverse} packages"
)

communicating_notes <- c(
  "Award-winning speaker with over 5 years teaching experience",
  "Produces professional, reproducible documents with R Markdown and Quarto",
  "Writes technical yet accessible content and documents; PhD thesis and blog posts described as accessible"
)

skills <- tibble::tribble(
  ~skill, ~statement,
  "R Programming", r_notes,
  "Statistics & Machine Learning", "Bayesian methods, linear and flexible regression, Bayesian optimisation, clustering, classification, inference, prediction", # nolint: line length linter.
  "Communicating", communicating_notes,
  "Software Development Toolkit", "Linux, Git, CI/CD, Command line",
  "Other languages & Software", "LaTeX, Stan, MATLAB, SLURM"
)
skills %>%
  detailed_entries(
    what = skill,
    why = statement
  )
```

# Extra Curricular & Service

```{r service}
rss_notes <- c(
  "Active member of the Royal statistical society; organised a variety of in-person and online events; collaborating with Head of Conferences and Events to organise conference sessions", # nolint: line length linter.
  "Previously member \\& Chair of the Young Statisticians Section; supporting early-career statisticians and data scientists, overseeing a team of 12 volunteers", # nolint: line length linter.
  "Treasurer \\& committee member for North Eastern Local Group"
)

cv_stats <- get_stack_user("283201")
cv_rep <- cv_stats$reputation
cv_badges <- cv_stats %>%
  dplyr::mutate(
    badge_sum = rowSums(dplyr::pick(dplyr::starts_with("badge")))
  ) %>%
  dplyr::pull("badge_sum")
todays_date <- lubridate::today()
todays_date_friendly <- glue::glue(
  "{lubridate::month(todays_date, label = TRUE, abbr = FALSE)} {lubridate::year(todays_date)}"
)


misc_notes <- c(
  "Participate in \\#TidyTuesday data visualisation challenge to practise visualisation and learn new-to-me R packages; see \\href{https://github.com/jcken95/tidytuesday}{GitHub repository}", # nolint: line length linter.
  glue::glue("Top 5\\% overall contributor on Crossvalidated. As of {todays_date_friendly} gained {cv_stats$reputation} reputation and {cv_badges} badges") # nolint: line length linter.
)

service <- tibble::tribble(
  ~job, ~start, ~end, ~institution, ~details,
  "Fellow \\& Volunteer", "2019", "Today", "Royal Statistical Society", rss_notes,
  "Things I do because I love stats, data and computers", "", "", "Projects \\& Online Activity", misc_notes,
)
service %>%
  detailed_entries(
    what = job,
    when = glue::glue("{start} - {end}"),
    with = institution,
    why = details,
    .protect = FALSE
  )
```

# Interests

```{r interests}
professional_interests <- c(
  "Technical: Bayesian methods; data visualisation; modelling; reproducibility; best practices",
  "Non-technical: Supporting early-career statisticians and data scientists; communicating statistics"
)

interests <- tibble::tribble(
  ~area, ~interests,
  "Professional", professional_interests,
  "Personal", "Cycling, hiking, running, you know, getting covered in mud"
)
interests %>%
  detailed_entries(
    what = area,
    why = interests
  )
```